JP2012138000A - Method for optimizing food material transportation network - Google Patents

Abstract

PROBLEM TO BE SOLVED: To optimize a food transport network capable of optimizing a food transport network so as to achieve optimum economic efficiency and evaluating the effectiveness of strengthening and improving the transport means for the loss of food or supply shortage at a demand destination. I will provide a.
SOLUTION: The freshness deterioration rate of the selected food, the maximum transport capacity for each type of transport means, the average speed and the temperature of the food during transportation, the position of the supply source and the freshness deterioration during unloading, the position of the collection delivery center And upper limit of freshness deterioration of ingredients at the time of receipt, increase value of freshness deterioration of ingredients in the collection and delivery center, location and demand of customers and the upper limit of freshness deterioration degree of ingredients at the time of acceptance, freshness Enter the sales price of the food according to the degree of deterioration, the transportation cost for each type of transportation and the data of the constraint condition, the amount of food transportation as the optimization variable, and the total profit of the whole food transportation network as the objective function, The transport amount for each type of transport means that maximizes the objective function under each input condition is calculated.
[Selection] Figure 1

Description

  The present invention relates to a method for optimizing a food transport network for transporting fresh food from a production area to a consumption area (including a final processing area).

  In general, foods such as agricultural products and seafood called fresh foods are basically those whose freshness decreases with time. The rate of decline in freshness varies greatly depending on the environment in which food is placed, such as temperature, humidity, and sunlight, and cold chains are being developed to minimize these deterioration factors.

  However, in areas where storage conditions and transportation conditions are not sufficiently established, there are cases where many foodstuffs are disposed of. In order to cope with the food crisis problem accompanying the ongoing population explosion on a global scale, minimizing food loss is also an important issue.

  Conventionally, in order to reduce food loss, in addition to the cold chain, the production volume is limited to meet market demands, unnecessary parts of the food are reused as fuel and chemical raw materials, expiration dates and unsold products These ingredients are used as fertilizer, livestock feed, or biomass energy.

  Also, for example, as described in Patent Document 1, using an IT network, producers and consumers are connected by a network, and food is quickly distributed while maintaining a balance between supply and demand. A system has also been proposed.

JP 2007-87351 A

  The freshness of foods has the property of deteriorating over time, and the deterioration rate tends to increase as the temperature rises, so under the appropriate conditions that maintain freshness, from the production area to the consumption area It is necessary to distribute.

  Conventionally, the freshness of ingredients is judged by relying on professionals, and it is difficult for amateurs to judge the degree of deterioration of freshness. Since no consideration was given to optimizing the entire series of transportation systems, there was a problem in that the profits of food sales were small, resulting in loss of foodstuffs and supply shortages at the customers.

  Therefore, the present invention can optimize the food transport network from the food supplier to the customer so as to achieve the optimum economy within the constraints of the type of transport means and the capacity, as well as the loss and demand of the food. It is an object of the present invention to provide a food transport network optimization method that can evaluate the effectiveness of strengthening and improving transportation means against shortage of supply.

  The method for optimizing the food transport network of the present invention provided for the above-described object includes the step of inputting a model function defining the freshness degradation rate of the food selected as an optimization target to a computer, and For each type of transport means used for transporting food, the step of inputting the maximum transport capacity, the average speed and the temperature of the food during transport, the position of the source node that is the source of the food, the food at the node A step of inputting the supply amount of the food and the freshness deterioration degree of the food at the time of carrying out; the position of the utility node serving as the food collection and delivery center; the upper limit value of the freshness deterioration of the food at the time of receipt at the node; A step of inputting an increase value of the freshness deterioration degree of the food in the computer, and The step of inputting the position of the sink node, the demand amount of the food at the node, and the upper limit of the freshness deterioration degree of the foodstuff at the time of acceptance, and the sales price of the foodstuff determined according to the freshness deterioration degree is input to the computer A step of inputting a transportation cost for each type of transportation means to the computer, a step of inputting a constraint condition between nodes for each type of transportation means to the computer, and a step of inputting each node to the computer With the amount of food transport between the optimization variables and the total profit obtained by subtracting the total transportation cost from the total sales at the sink node as the objective function, under each condition entered in each step, This comprises the step of calculating the transport amount between each node for each type of transport means so as to maximize the objective function.

  According to the method for optimizing a food distribution system according to the present invention, it is possible to improve the efficiency of a food transport network between a food supply source (source node) and a demand destination (sink node) and increase sales profit of the food. At the same time, it is possible to find a bottleneck in food transportation and evaluate the effectiveness of strengthening and improving transportation means to eliminate food loss and supply shortage at the customers.

It is a flowchart which shows roughly the process sequence by the computer for enforcing the foodstuff transportation network optimization method of this invention. It is a graph which shows typically the tendency of the freshness degradation of a foodstuff by the difference in environmental temperature. It is the graph which showed the relationship between temperature and the freshness degradation speed with the plot value on the semilogarithmic graph. It is the figure which plotted each position of a production place, a collection delivery center, and a consumption place on a coordinate.

  The food transport network optimizing method of the present invention uses various transport means (trucks, trucks, etc.) in order to maximize the profit on the production side when transporting food from a supplier such as a production area to a demand destination such as a consumption area. It provides a method for optimizing the transportation volume of trains, etc., and enables evaluation of the effectiveness of strengthening and improving transportation means against food loss and supply shortages at demand destinations. In the present invention, the optimization calculation of the transport amount of each transport means is executed by the general-purpose computer according to the procedure shown in FIG. The outline of the present invention will be described below with reference to FIG.

(S1)
In the present invention, first, fresh food materials such as agricultural products and seafood to be analyzed are selected, and freshness deterioration data of the food materials are input to a computer. Here, a relational expression between the freshness deterioration rate of the food and the temperature is input to the computer and stored. Details will be described later.

(S2)
Next, input the specifications and capabilities of the vehicle. Here, one or more types of transportation means that can be used for transporting foods are selected, and the maximum transport capacity, average speed, and food temperature during transportation are input to a computer and stored. Details will be described later.

(S3)
Next, node data is input. Here, as will be described in detail later, a node includes a source node (food supply source), a sink node (food demand destination), and a utility node (collection / delivery center). These names are input to a computer and stored. Let

  Moreover, in each source node, the freshness at the time of a foodstuff being carried out from these is input and memorize | stored in a computer. In each sink node and utility node, the limit freshness level at which food can be received is input to the computer and stored at the time of loading into these nodes.

  Further, the time required for transportation between each sink node or utility node is input to the computer from each source node or utility node and stored.

(S4)
Next, economic evaluation data is input to the computer. Here, the relational expression between the freshness of the ingredients and the selling price at the time of carrying in to the demand destination is inputted and stored. Moreover, the fare of each transportation means is input and stored. Details will be described later.

(S5)
Next, various constraint conditions are input and stored in the computer. The constraints include quantitative constraints, qualitative constraints, and food transport network constraints. Here, the quantitative restriction condition is a restriction condition imposed in consideration of a quantitative balance among the production amount, the consumption amount and the transportation amount.

  Further, the qualitative constraint condition is a constraint condition imposed in consideration of satisfying the freshness required in the consumption area. In addition, the food transport network constraint condition is a constraint condition that is imposed in consideration of constraints related to connection between specific nodes. Details of these constraints will be described later.

(S6)
The computer performs optimization calculation of the transportation amount for each transportation means based on the data respectively inputted in the above-described (S1) to (S5).

(S7)
The computer outputs the optimal solution obtained by completing the optimization calculation to an output device such as a monitor screen or a printer, and ends the process.

  With the above procedure, how efficiently the produced food can be delivered to the consumption side under the geographical, transportation capacity, and economic conditions in the assumed area. In addition, it is possible to grasp the balance of the entire food transport network in terms of how much food is lost (or if there is a supply shortage).

The optimum solution obtained in this way is examined, and if necessary, such as when a food loss or supply shortage occurs, the input data is changed and the calculation is repeated.
Hereinafter, the present invention will be described in more detail.

(Quality definition)
The measure of freshness of ingredients has an important impact on the freshness commonly used in fruits and vegetables such as vegetables and seafood (sometimes expressed by ATP, k value, etc.) and the taste of meat. There are various things such as maturity and other shapes and shades that are not directly related to taste, but especially when dealing with food transportation issues, how to maintain freshness is the most important Conceivable.

  Among foodstuffs, for example, the freshness of fruits and vegetables is generally the highest immediately after harvesting, and has a property of decreasing with time. On the other hand, there is a view that varieties that require ripening after harvest, such as tomatoes and melons, should not be deteriorated in freshness in the time range until the best time to eat them.

  Once fresh, the freshness cannot be regenerated. There are cases where leaf vegetables are soaked in cold water to absorb water, but it is thought that freshness will not return, anyway, deterioration of freshness will depend on the time and the environment where the ingredients are placed it is conceivable that.

If changes in the freshness of food (degree of deterioration) can be quantitatively expressed by elapsed time and environmental variables (temperature, humidity, etc.), quality other than freshness can be handled in the same manner.
Therefore, the freshness degradation degree is introduced as an index of freshness, and this is defined as follows.
Degree of freshness degradation = f (time, environmental condition) Here, f means function.

As environmental conditions, temperature, humidity, vibration, light, air composition (oxygen concentration, ethylene concentration) and the like are considered to be affected, but in general, the influence of temperature is large. Therefore, when the freshness deterioration can be expressed only by the elapsed time and temperature, the freshness deterioration degree is expressed by the following equation.
Degree of freshness = f (time, temperature)

  In the case of fruits and vegetables, the cause of the deterioration of freshness is said to be due to a change in composition in order to use sugars and organic acids stored inside to maintain life as a respiratory substrate. In the case of fish, it is said that the cause is that the decomposition of proteins and the like proceeds by the action of autolytic enzymes.

  In order to suppress such metabolism and decomposition, it has been practiced to store at a low temperature or enclose nitrogen to suppress a decrease in freshness. In the case of holding at a low temperature, it is necessary to manage the temperature within a temperature range that does not cause a low-temperature failure, but within that range, the lower the temperature, the longer the freshness.

  Metabolism and decomposition are a kind of chemical reaction, but the rate of these chemical reactions is generally often expressed by an Arrhenius-type reaction rate equation. Therefore, the following zero-order Arrhenius equation may be used as one of model equations for approximating the freshness deterioration rate of food.

k = Aexp (B / T)
In the above formula, k is a freshness degradation rate constant, and in this case, it is equal to the freshness degradation rate. A and B are parameters, and T is an absolute temperature.

In addition, here, for convenience, a scale as shown in Table 1 is provided as the degree of freshness degradation for generalization.

The freshness degradation degree (frequency) shown in Table 1 is an example of typical points, and the points shown in the table are continuously interpolated. For example, the freshness degradation level = 1.5 means a freshness level between 0 and 3.
In this case, the parameters A and B in the above-mentioned Arrhenius-type expression representing the freshness degradation rate constant k are determined from the experience and measured data of the skilled worker in accordance with the scale of the degree of freshness degradation.

  FIG. 2 is a graph schematically showing a tendency of freshness degradation due to a difference in environmental temperature. Here, the temperature dependence of the freshness degradation rate may be approximated using the above-mentioned Arrhenius-type reaction rate equation, and the approximation formula of the freshness degradation rate is not limited to this. The coefficient (parameter) of each term may be determined based on experience and actual measurement data so as to match the frequency scale of Table 1. Here, what approximate expression is adopted as the model function may be determined on a case-by-case basis.

(Node definition)
Here, the basic bases existing in the food transport network in the area to be optimized are called nodes. There are three types of nodes: source (source node), sink (sink node), and utility (utility node).

  Here, the source means a place where a food source is provided, such as a food production area or a harvest area, or a port serving as a food import base. In addition, the sink means a food consumption place, a final processing place where the food is finally processed, and a food demand destination such as a port serving as a food export base. Further, the utility means a collection and distribution center or the like that is interposed between the source and the sink and through which food passes during transportation. Table 2 shows the specifications of each node in this embodiment.

  In Table 2, the number of each node is represented by Nsrc for the source, Nsnk for the sink, and Nutl for the utility. This table shows a case where there are three sources (Nsrc = 3), five sinks (Nsnk = 5), and two utilities (Nutl = 2).

The specifications of each node are determined based on quantitative and qualitative things. The quantitative specifications are as follows.
Pp: p = 1 to p = represents the supply amount (supply capability) of food from each source of Nsrc. Pp corresponds to the production volume if the source is the production area, and the import volume if the source is import. It is assumed that supply from each source cannot exceed the supply amount determined there.

  Sq: Indicates the food consumption (consumption capacity) of each sink of q = 1 to Nsnk. Sq corresponds to the consumption demand of food when the node is a consumption area, and the processing capacity of the processing factory when the node is the final processing factory. Each sink cannot accept more food than specified.

  Mr: r = 1 ~ Indicates the processing capacity of each utility of Nutl. Each utility cannot accept more ingredients than specified.

  Here, the amount of food can be expressed in weight units or bulk units. Which one to select is determined according to the characteristics of the food to be handled. In addition, the moisture content of the food may change somewhat during transportation, but here, the food content is expressed on the basis of the moisture content at the time of shipment from the source.

The qualitative specifications are as follows.
XPp: Represents the freshness at the time of shipment of ingredients supplied from each source of p = 1 to Nsrc.
XSq: Represents the minimum required freshness (consumption limit freshness) at the time of import of the ingredients accepted by each sink of q = 1 to Nsnk.
XMIr: r = 1 to Nutl Indicates the minimum required freshness (acceptance limit freshness) at the time of import of foods accepted by Nutl.
XMOr: Denotes the freshness of the ingredients sent by each utility from r = 1 to Nutl.

(Transport time between nodes)
Here, the geographical coordinates of each node are considered fixed. That is, the production area, the consumption area, the collection / delivery center, the processing factory, and the like are assumed to be fixed at specific geographical coordinates. In addition, when transporting ingredients between nodes, the time required for each means of transportation varies depending on traffic congestion and weather (snow, wind), etc. The time required is fixed.

  Example 1: Non-refrigerated vehicle transportation (not equipped with refrigeration equipment) at a distance of 100 km from production area A to consumption area B is expected to run at an average speed of 40 km, with an operation time of 2.5 hours, and an average of 30 minutes required for loading and unloading Then, the total time required is 3 hours.

  Example 2: Refrigerated freight train transportation at a distance of 320 km from the collection and delivery center P to the consumption area Q is expected to have an average speed of 80 km, and the operation time is 4 hours, and the total time required is 1 hour for loading and unloading. Is 5 hours. As in these examples, the time required between any nodes can be determined for each available vehicle.

(Freshness deterioration due to transportation)
Next, as described above, the freshness degradation occurring within the required time determined for each transportation means between arbitrary nodes is obtained.

  Example 1: In the above three-hour non-refrigerated vehicle transportation from the production area A to the consumption area B, assuming that the temperature is 30 ° C and the freshness deterioration rate at 30 ° C is 0.5 degrees / h, The degree of freshness degradation is 1.5. If the degree of freshness deterioration at the time of shipment from the production area A is 0.5, the degree of freshness deterioration at the time of delivery to the consumption area B is 2.0.

  Example 2: In the refrigerated freight train transport for 5 hours from the above distribution center P to the consumption area Q, if the average temperature is 10 ° C and the deterioration rate at 10 ° C is 0.3 degrees / h, 5 The degree of freshness degradation over time is 1.5. If the degree of freshness deterioration at the time of carrying out from the delivery center P is 2.0, the degree of freshness deterioration at the time of carrying into the consumption area Q is 3.5.

(Variable definition)
(1) Transportation volume (independent variable)
The independent variable on the food transport network is the transport amount V between the nodes. Further, some of the freshness X at the time of carry-out of the food to be transported and freshness Y at the time of carry-in are fixed parameters, but some are dependent variables determined according to the transport amount V.

As an example, Table 3 shows the transport amount variables between nodes when Nsrc = 3, Nsnk = 3, and Nutl = 2.

  In Table 3, for example, V1,1, z is the transport amount from Src, 1 (first source) to Snk, 1 (first sink) by the zth transport means. For example, Z = 1 is non-refrigerated vehicle transport and Z = 2 is refrigerated freight train transport.

  Here, it is assumed that there is basically no transportation between utilities. However, transportation between different utilities may be beneficial, and in such a case, a transportation variable may be defined only between different utilities.

The number of transport variable V defined in Table 3 is 25. If the number of means of transport Z is Nz, a total of 25 × Nz variables are defined. If you define the variable again here,
Vi, j, z: i = 1 to Nsrc + Nutl, j = 1 to Nsnk + Nutl, z = 1 to Nz

Table 4 shows the supply sources of foods to be transported defined by the above variables.

Table 5 shows the supply destinations of the foods to be transported defined by the variables.

(2) Freshness when carrying out (partly dependent variable)
Next, Table 6 shows the freshness of the ingredients carried out from each node when Nsrc = 3 and Nutl = 2.

  In Table 6, since XP1 to XP3 are freshness at the time of shipment from the production area, they can be fixed values. For XMO1 and XMO2, the freshness is equal to the freshness at the time of loading into each node, or the freshness considering the degradation with the holding time in the node.

3) Freshness at delivery (partly dependent variable)
Similarly, Table 7 shows freshness variables at the time of loading for each transportation means of foods transported between nodes when Nsrc = 3, Nsnk = 3, and Nutl = 2.

  Here, Y1,1, z is freshness at the time of carrying in the foodstuff transported from Src, 1 (first source) to Snk, 1 (first sink) by the z-th transport means. According to Example 1 above, when z = 1 (non-cooled vehicle) is used as the means of transportation, the freshness deteriorates by 1.5 during transportation for 3 hours, so it is calculated as Y1,1,1 = XP1 + 1.5 . In this case, since XP1 is a fixed value, Y1,1,1 is also a fixed value.

  Similarly, Y4,3, z is the freshness at the time of carry-in of the foodstuff transported from Utl, 1 (first Utility) to Snk, 3 (third Sink) by the zth transport means. Similarly, according to Example 2 above, when z = 2 (refrigerated freight train) is used as the means of transportation, the freshness deteriorates by 1.5 during the 5-hour transportation, so Y4,3,2 = XMO1 + 1.5 Is done. In this case, since XMO1 is a dependent variable that changes depending on the state of loading into Utl, 1, Y4,3,2 are also dependent variables.

  As for the utility node, if all the ingredients to be brought in are from the source, Yi, j, z: i = 1 for all means of transportation z from all sources from Src, 1 to Src, 3 to Nsrc, z = 1 to Nz is uniquely determined. Since each sink and utility node has a standard for the minimum required freshness at the time of carry-in, a route whose freshness falls below that standard becomes invalid.

ここで、
Σj,z (Vi,j,z)は、変数Vi,j,zをiは固定で、jとzについて足し合わせた合計値を意味する。
Σi,z (Vi,j,z)は、変数Vi,j,zをjは固定で、iとzについて足し合わせた合計値を意味する。
Σi,j, (Vi,j,z)は、変数Vi,j,zをzは固定で、iとjについて足し合わせた合計値を意味する。 (Quantitative constraints)
Table 8 shows the quantitative constraints imposed on the food transport variables.

here,
Σj, z (Vi, j, z) means a total value obtained by adding the variables Vi, j, z to i and fixing j and z.
Σi, z (Vi, j, z) means a total value obtained by adding the variables Vi, j, z to j and i and z.
Σi, j, (Vi, j, z) means a total value obtained by adding the variables Vi, j, z to z and fixing i and j.

(Quality constraints)
Table 9 shows the qualitative constraints imposed on the food transport variables.

(Food transport network constraints)
As a constraint condition in the food transport network, for example, a condition that a cold car can be used only from the collection and delivery center can be considered as a network constraint.
Specifically, the range of values that Vi, j, z can take is limited. For example, by setting the value of a specific combination of i, j, and z in Table 3 described above to 0, transportation by the z means between the source i and the sink j can be cut off.

(Objective function)
Here, the optimization objective function is defined so that the profits obtained by improving the food transportation network are maximized.
The profit as the objective function is considered to be obtained by subtracting expenses (here, transportation costs) from sales of foodstuffs. For processed products, it shall contribute to sales at a unit price including processing costs.

  The role of the food transportation network is to deliver foods from the production area to the consumption areas with a certain level of freshness maintained, and to some foods that are processed and sold as processed foods. Assume that

(1) Sales Basically, sales are the unit price (price) of ingredients multiplied by the sales volume. Here, it is assumed that the sales quantity is equal to the amount of food arriving at the consumption place or the final processing place. In the case of foodstuffs, unsold goods may actually occur in the final consumption area, but here, the ingredients produced as a food transportation network are used as local distributors (retailers, wholesalers in the final consumption area). Etc.).

  The price of the transported food is evaluated by the freshness at the time of arrival at the destination, and it is considered that the higher the freshness, the higher the selling price can be set. Therefore, the relationship between the price of food and freshness is set for each destination as follows.

Sales price = Gj (freshness degradation), j = 1 to Nsnk
Here, G means a function, and for example, a selling price as shown in the following equation can be assumed.
Gj = aj + (6-degradation of freshness) x bj yen / t
j = 1to Nsnk, aj, bj are constants.

  When the customer is the final processing plant, the selling price is determined by the value of the processed product, so the price is determined regardless of the degree of deterioration of freshness. For example, when the demand destination of j = 2 is a processing place, the value of the processed product itself is given regardless of freshness, such as a2 = 100,000, b2 = 0 (including processing wage).

  However, there is a certain limit to the freshness of food suitable for processing. Thus, sales of ingredients are Σi, j, z (Vi, j, z × Gj (Yi, j, z)), i = 1 to Nsrc + Nutl, j = 1 to Nsnk, z = 1 to Nz Desired.

(2) Transportation costs Trucks, freight trains, etc. are used as a means of transporting food. These transportation costs can be calculated by integrating the fare required to transport a unit amount (1t) per unit distance (1km).
Fare = Fz, z = 1 to Nz (yen / t ・ km)

Thereby, the transportation cost for each transportation means z is obtained by the following equation.
Fz × Σi, j (Vi, j, z), i = 1 to Nsrc + Nutl, j = 1 to Nsnk + Nutl
Therefore, the total transportation cost is calculated by the following formula.
Σz (Fz × Σi, j (Vi, j, z)), z = 1 to Nz
Actually, there is a possibility that the fare may fluctuate depending on the loading condition of trucks and freight trains, but such a fluctuation is not considered when performing macro optimization.

(3) Objective function From the above, the objective function (profit) to be optimized is expressed as follows.
Objective function = Σi, j, z (Vi, j, z × Gj (Yi, j, z)) -Σz (Fz × Σi, j (Vi, j, z)), i = 1 to Nsrc + Nutl, j = 1 to Nsnk + Nutl, z = 1 to Nz

  Next, an embodiment of the food transport network optimization method of the present invention will be described. In addition, the Example described below is a case assumed according to the present condition, and is not an actual thing.

Example 1
(A1) Selection of ingredients Here, a certain vegetable is selected as a representative fresh food.
(A2) Input of Freshness Degradation Data Here, it is assumed that data as shown in Table 10 is obtained regarding the correspondence between temperature and freshness degradation rate.

  FIG. 3 shows the relationship between the temperature and the freshness deterioration rate in Table 10 plotted on a semilogarithmic graph. The straight line in the figure approximates the relationship between the deterioration rate and the temperature based on the plot data, and the deterioration rate can be approximately calculated by the following model function.

Freshness degradation rate = 10 ^ (0.0111 x temperature-0.641)
In this case, assuming that the transport temperature of the non-cooled vehicle is 30 ° C. and the transport temperature of the cold vehicle is 0 ° C., the deterioration rates of the freshness of the vegetables are 0.492 degrees / h and 0.229 degrees / h, respectively.

(A3) Input of transportation means and transportation capacity Here, it was assumed that two types of transport vehicles, that is, a non-cooled vehicle and a cooled vehicle, can be used as the transportation means. Each maximum carrying amount was set to t · km / d, that is, the capacity of how many tons of vegetables per day can be carried as shown in Table 11.

ここで、これらの運搬車の運行速度は何れも平均２５ｋｍ／ｈと想定した。なお、非保冷車の運搬温度を30℃、保冷車の運搬温度を0℃とすると、それぞれの劣化速度は、前記鮮度劣化速度の式より0.492 度/h、0.229度/hとなる。

Here, the operation speed of these transport vehicles is assumed to be an average of 25 km / h. If the transport temperature of the non-cooled vehicle is 30 ° C. and the transport temperature of the cool vehicle is 0 ° C., the deterioration rates are 0.492 degrees / h and 0.229 degrees / h from the formula for the freshness deterioration rate.

(A4) Input of Node Data Next, FIG. 4 shows a state in which the position of each node (production place, collection / delivery center, consumption place) is plotted on coordinates. As nodes, three production sites (see Table 12), two collection and distribution centers (see Table 13), and three consumption sites (see Table 14) were assumed.

これらの生産地からは、採れたて（搬出時鮮度０）の野菜を出荷するものとした。

From these production areas, freshly picked vegetables (freshness at the time of carrying out) were shipped.

これらの集荷配送センターでは、鮮度が２以上に低下した野菜は受け入れないものとする。また、集荷配送センターへ搬入される野菜の鮮度劣化度が最も高い（最も鮮度が落ちている）ものを基準とし、センター内での積み替え時に、鮮度が０．５劣化（鮮度劣化度が０．５だけ増加）して搬出されるものとした。

These collection and distribution centers will not accept vegetables whose freshness has fallen to 2 or more. In addition, the freshness deterioration degree of the vegetables brought into the collection and delivery center is the highest (the freshness is the lowest), and the freshness is deteriorated by 0.5 (freshness deterioration degree is 0. 0) when transshipping in the center. And increased by 5).

これらの消費地では、鮮度劣化度が６以上のものは受け入れないものとした。

In these consumption areas, those with a freshness deterioration degree of 6 or more were not accepted.

Next, Table 15 shows the distance between each node. In this embodiment, the distance between the nodes is set to 1.5 times the geographical linear distance for convenience.
In actual analysis, the actual transport distance may be obtained and input in consideration of local road conditions and the like.

Further, as described above, since the operation speed of each transport vehicle is assumed to be an average of 25 km / h, the required transportation time between the nodes is calculated as shown in Table 16.

(A5) Input of economic evaluation data In the sales price calculation formula Gj = aj + (6-freshness deterioration degree) × bj yen / t described above, here, a = 10,000, b = 30,000 It was assumed that the coefficients of Therefore, the selling price for each freshness deterioration degree is calculated as shown in Table 17.

On the other hand, the transportation cost is given as shown in Table 18.

同表は、集荷配送センター間の運搬は行わないことを意味する。 (A6) Food transport network constraint conditions Table 19 shows the constraint conditions for non-refrigerated vehicles.

This table means that transportation between collection and distribution centers is not performed.

同表は、生産地からは保冷車を使用することができないことと、収集センター間は運搬を行わないことを意味する。 Next, Table 20 shows the constraint conditions of the cold-reserved vehicle.

The table means that a cold truck cannot be used from the production area and that no transportation is performed between collection centers.

(A7) Implementation of Optimization Calculation with Restriction Conditions Optimization calculation was performed based on the input data (A1) to (A6) described above. here,
The transport amount (t / d) between each node was optimized to maximize the value of the following objective function.
Objective function: Gross profit = Sales-Transportation cost

(A8) Confirmation of optimum solution Table 21 shows the optimized inter-node transportation amount of the non-cooled vehicle.

Table 22 shows the optimized inter-node transportation amount of the cold car.

生産地Ｐ−２と生産地Ｐ−３でロスが発生し、特に生産地Ｐ−２では、生産量の１００％が無駄になっている。 Table 23 shows the situation of carrying out the production area.

Loss occurs in the production area P-2 and the production area P-3, and particularly 100% of the production amount is wasted in the production area P-2.

集荷配送センターC−1は利用されていない。 Table 24 shows the loading / unloading status of the collection / delivery center.

The collection / delivery center C-1 is not used.

消費地Ｓ−2と消費地Ｓ−3には、供給されていない。 Table 25 shows the supply status to the consumption areas.

It is not supplied to consumption place S-2 and consumption place S-3.

Table 26 shows the degree of freshness degradation when each node is carried out.

Table 27 shows the degree of freshness deterioration at the time of delivery to each node by a non-cooled vehicle.

Table 28 shows the unit sales price of each non-cooled vehicle to each node.

Table 29 shows the sales to each node by the non-cooled vehicle.

Table 30 shows the fare to each node by the non-cooled vehicle.

Table 31 shows the degree of freshness deterioration at the time of carry-in to each node by a cold car.

Table 32 shows the unit sales price to each node by the cold truck.

Table 33 shows the sales to each node by the cold truck.

Table 34 shows the fares to each node by the cold car.

As a result, the gross profit was 5,067,192 yen per day as shown in Table 35.

(Example 2)
In Example 1 mentioned above, there was much loss of foodstuffs and the demand of the consumption place was not able to be satisfied. Therefore, in the present embodiment, assuming that the road infrastructure is improved and improved, the case where the operation speed of the transport vehicle is changed from the previous 25 km / h to 50 km / h is the same as in the first embodiment described above. Perform optimization calculations in steps.

(B1) Selection of foodstuff It applies to (A1) of Example 1 mentioned above.
(B2) Input of Freshness Degradation Data Same as (A2) of Example 1 described above.

(B3) Input of transportation means and transportation capacity Here, the conditions of the transportation means conform to (A3) of Example 1 described above, but the operation speed of the transport vehicle was assumed to be 50 km / h on average.

(B4) Input of node data The conditions of the node are also in accordance with (A4) of Example 1, but since the average operation speed of the transport vehicle is assumed to be 50 km / h, the transport time between each node is shown in Table 36. It is changed as follows.

(B5) Input of economic evaluation data Same as (A5) of Example 1 described above.
(B6) Input of Food Transport Network Restriction Conditions According to (A6) of Example 1 described above.
(B7) Implementation of Optimization Calculation with Restriction Conditions Optimization calculation was performed based on the input data (B1) to (B6) described above. The objective function optimized the transport amount (t / d) between each node according to (A7) of Example 1.

(B8) Confirmation of optimum solution Table 37 shows the optimized inter-node transportation amount of the non-cooled vehicle.

Table 38 shows the optimized inter-node transportation amount of the cold truck.

運搬車の運行速度が上がったことにより、ロスが解消されている。 Table 39 shows the carry-out status of the production areas.

Loss has been eliminated by increasing the speed of transportation vehicles.

Table 40 shows the loading / unloading status of the collection / delivery center.

上記の表に示すように、需要も全て満たされている。 Table 41 shows the supply status of foodstuffs to consumption areas.

As shown in the table above, all demand is also met.

Table 42 shows the degree of freshness degradation at the time of carry-out of each node.

Table 43 shows the degree of freshness deterioration at the time of delivery to each node by the non-cooled vehicle.

Table 44 shows the unit sales price of each non-cooled vehicle to each node.

Table 45 shows the sales to each node by the non-cooled vehicle.

Table 46 shows the fare to each node by the non-cooled vehicle.

Table 47 shows the freshness deterioration degree at the time of carry-in to each node by the cold truck.

Table 48 shows the unit sales price to each node by the cold truck.

Table 49 shows the sales to each node by the cold truck.

Table 50 shows the fare to each node by the cold car.

As a result, the gross profit was 11,434,781 yen per day as shown in Table 51.

Example 3
Here, it is assumed that the cold-reserved vehicle can be used after being transported from the production area.
(C1) Selection of foodstuff It applies to (A1) of Example 1 mentioned above.
(C2) Input of Freshness Degradation Data Same as (A2) of Example 1 described above.
(C3) Input of transportation means and transportation capacity According to (A3) of the first embodiment described above.
(C4) Input of node data Same as (A4) in the first embodiment.
(C5) Input of economic evaluation data Same as (A5) of Example 1 described above.

(C6) Input of food transport network constraint condition The non-cooled vehicle conforms to (A6) of the first embodiment described above. In addition, Table 52 shows the food transport network restriction conditions for the cold-reserved vehicle.

上記の制約は、集荷配送センター間の運搬を行わないことは、実施例１と同じであるが、食材を生産地から直接保冷車で搬出できるようになったことを意味する。

The above restrictions are the same as in Example 1 that the transportation between the collection and distribution centers is not performed, but it means that the food can be directly carried out from the production area by a cold car.

(C7) Implementation of constrained optimization calculation Optimization calculation was performed based on the input data of (C1) to (C6) described above. The objective function optimized the transport amount (t / d) between each node according to (A7) of Example 1.

(C8) Confirmation of optimum solution Table 53 shows the optimized inter-node transportation amount of the non-cooled vehicle.

Table 54 shows the optimized inter-node transportation amount of the cold truck.

上記の表に示すように、本実施例の場合には、生産地Ｐ−２でロスが発生している。 Table 55 shows how the production areas were carried out.

As shown in the above table, in the case of this example, a loss occurs at the production site P-2.

Table 56 shows the loading / unloading status of the collection / delivery center.

この場合には、消費地Ｓ−３への搬入が無くなっている。 Table 57 shows the supply status to the consumption areas.

In this case, there is no carry-in to the consumption area S-3.

Table 58 shows the degree of freshness degradation at the time of carry-out of each node.

Table 59 shows the degree of freshness deterioration when each non-cooled vehicle is brought into each node.

Table 60 shows the unit sales price of each non-cooled vehicle to each node.

Table 61 shows sales to each node by the non-cooled vehicle.

Table 62 shows the fare to each node by the non-cooled vehicle.

Table 63 shows the degree of freshness deterioration at the time of carry-in to each node by the cold car.

Table 64 shows the unit sales price to each node by the cold truck.

Table 65 shows the sales to each node by the cold truck.

Table 66 shows the fares to each node by the cold car.

As a result, as shown in Table 67, the gross profit was 9,757,695 yen per day.

  The food transport network optimization method of the present invention is a food produced while achieving optimum economic efficiency within the restrictions on the types and capabilities of food transport means from the production area to the consumption area within the specified area. It can be effectively used as a method to provide quantitative guidelines for strengthening and improving transportation means in order to reduce losses and supply shortages in consumption areas.

Claims (1)

Inputting a model function defining the freshness degradation rate of the food selected for optimization into a computer;
For each type of transportation means used for transporting the food, the computer inputs a maximum transport capacity, an average speed, and a food temperature during transport;
Input to the computer the position of the source node that is the supply source of the food, the supply amount of the food at the node, and the freshness deterioration degree of the food at the time of carry-out;
Inputting the position of a utility node serving as a food collection and delivery center to the computer, an upper limit value of the freshness deterioration degree of the foodstuff at the time of receipt at the node, and an increase value of the freshness deterioration degree of the foodstuff in the node;
Inputting the position of the sink node that is the demand destination of the food, the demand amount of the food at the node, and the upper limit of the freshness deterioration level of the food at the time of acceptance to the computer;
Inputting the sales price of the ingredients determined according to the degree of freshness deterioration to the computer;
Inputting the transportation cost for each type of means of transportation into the computer;
Inputting into the computer a constraint between nodes for each type of means of transport;
In the computer, the amount of food transported between each node is an optimization variable, and the total profit obtained by subtracting the total transportation cost from the total sales at the sink node is used as an objective function to input each of the above steps. A method for optimizing a food transport network, comprising: calculating a transport amount between nodes for each type of transport means so as to maximize the objective function under conditions.

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