Innovative Technologies and Scientific Solutions for Industries, 2021
The subject of this research is distance and time of several city tour problems which known as tr... more The subject of this research is distance and time of several city tour problems which known as traveling salesman problem (tsp). The goal is to find out the gaps of distance and time between two types of optimization methods in traveling salesman problem: exact and approximate. Exact method yields optimal solution but spends more time when the number of cities is increasing and approximate method yields near optimal solution even optimal but spends less time than exact methods. The task in this study is to identify and formulate each algorithm for each method, then to run each algorithm with the same input and to get the research output: total distance, and the last to compare both methods: advantage and limitation. Methods used are Brute Force (BF) and Branch and Bound (B&B) algorithms which are categorized as exact methods are compared with Artificial Bee Colony (ABC), Tabu Search (TS) and Simulated Annealing (SA) algorithms which are categorized as approximate methods or known a...
Research of travel distance on single - depot position in warehouse is tremendous. This study foc... more Research of travel distance on single - depot position in warehouse is tremendous. This study focuses more on the effect of two-depot position on travel distance in order picking problem (OPP) by using the concept of traveling salesman problem (TSP) and exact method – Branch and Bound (B\&B) algorithm. The total distance of one-depot position is shorter than two-depot position for single and double block warehouses and the difference is less than 5%. The total distance is also compared with approximate methods – SA and TS which show that the differences are less than 5%. The sequence of location visit for one depot and two depot is similar about two third from the total location visits. For order picking problem that has more than 25 location visits, one need to consider to apply approximate approach to get the solution faster even the difference will be higher from exact approach when the number of location visit or aisle increases.
Perencanaan dan pengendalian produksi tidak hanya mengerjakan masalah perencanaan saja akan tetap... more Perencanaan dan pengendalian produksi tidak hanya mengerjakan masalah perencanaan saja akan tetapi sangat terkait dengan manajemen inventori.161 hlm.; 24 cm
Optimasi Jalur Distribusi dengan Metode Vehicle Routing Problem (VRP)
The purpose of the study was to apply the method of Vehicle Routing Problem (VRP) Method to accel... more The purpose of the study was to apply the method of Vehicle Routing Problem (VRP) Method to accelerate product distribution and minimize the use of fuel. The method of VRP is one of the solutions to find the shortest route from 57 locations in Jabodetabek (Jakarta, Bogor, Depok, Tangerang, Bekasi), four locations in Bandung, and three locations in Surabaya. The result shows that the most efficient method of VRP is by combining the heuristics and meta-heuristics – simulated annealing methods which reduce the distance about 11.79 % in Jabodetabek, 0 % in Bandung, and 8.98 % in Surabaya.
Analisis Waktu Picking dengan Menggunakan Zone System
Productivity in order picking time is continuously evaluated and analyzed, because mostly picking... more Productivity in order picking time is continuously evaluated and analyzed, because mostly picking is done manually by human. Zone system is one of the methods to increase productivity. In this research, zones is determined by a number of pickers and zone in warehouse is evaluated and divided into 1 zone to 3 zones, congestion and blocking factor are negligible, random storage assignment and S-Shape routing method are used. Total travel time is calculated by summing travel time within storage aisle, travel time in the cross aisle, setup time, and picking time. By comparing among all zones, the result indicates that when the number of zones increases, expected time to finish pick route will be decreased
Estimasi Trip Frequency Dengan Menggunakan Model Multiple Linear Regression
One important step in transportation planning is trip generation / trip frequency / trip producti... more One important step in transportation planning is trip generation / trip frequency / trip production. Factors that influences trip frequency are income, family size, and vehicle ownership. One has to know the relationship between trip frequency and its factors by building the statistical model. The model is Multiple Linier Regression which the dependent variable is trip frequency and the independent variables are income, family size and vehicle ownership
Penetapan pengalokasian Rest Allowance untuk pekerjaan konstruksi
Pekerja akan merasa lelah jika bekerja terus menerus dalam suatu periode tertentu sampai akhirnya... more Pekerja akan merasa lelah jika bekerja terus menerus dalam suatu periode tertentu sampai akhirnya tidak mampu lagi bekerja. Oleh karena itu perlu diberikan suatu tenggang waktu untuk mengembalikan energinya kembali. Tenggang waktu inilah yang dinamakan Rest Allowance atau Fatigue Allowance. Asumsi dalam penelitian ini adalah terbatasnya jumlah energy yang tersedia, output konstan, pekerja dalam keadaan sehat dan tidak merokok sewaktu bekerja. Ada dua cara untuk memberikan allowance tersebut, pertama yakni dengan langsung memberikan allowance untuk time study yang ditetapkan ILO yakni sebesar 4%, kedua adalah dengan menggunakan model energy metabolisme untuk usia tertentu. Penelitian dilakukan pada 70 pekerja, dimana pekerja itu mampu mengerjakan tugas konstruksi pemasangan bata, kayu dan mengecat. Kalkulasi rest allowance model energy metabolisme ditentukan oleh usia dan jenis kelamin, berat badan, jumlah jam tidur, jumlah jam kerja, dan standar energi yang dikeluarkan oleh masing-m...
Analysis of the Expected Cross Aisle Travel Distance: For Multi-Picks and Multi-Aisles Conditions
Purpose: The purpose of this research is to find the impacts of multi picks multi aisle on expect... more Purpose: The purpose of this research is to find the impacts of multi picks multi aisle on expected cross aisle traveldistance for one picker at layout with parallel picking aisles and orthogonal cross aisles at each end of the picking aisles.Design / methodology / approach: Using the theory of expected mean value to calculate expected number of cross aislewidth in multi-picks and multi-aisles conditionsFindings: the results show that the expected cross aisle travel distance is affected by the expected number of aisle widthand number of picksResearch limitations / implications: Further research is needed to explore the other type of layout in order to get theshortest distance. Secondly, the further research needs to analyze the picking activity is done by more than one pickerPractical implications: This is the early beginning study to get the shortest cross aisle travel distance that may be used forprofessional engineer to design and to choose the best layout for the condition – mul...
Estimasi Jarak Tempuh Order Picking System - Low Level to Part di PT. GMS
Travel distance has an important role in order picking system, low-level picker-to-part, especial... more Travel distance has an important role in order picking system, low-level picker-to-part, especially in warehousing productivity. Reducing travel distance means reducing travel time. Research was conducted at PT.GMS that uses random storage which means every item has an equal probability and every item is taken and used by production. Access frequency is assumed to be the same. Travel distance estimation is using probability calculation approach and combination with uniform distribution. Several methods are used to explore the shortest distance: Return Without Repetition, Midpoint Heuristics, and Traversal Without Skip. The results has shown that Midpoint strategy is better than Return Without Repetition and Traversal Without Skip.
Pengukuran Kinerja Gudang Dengan Menggunakan Metode Balanced Scorecard – Studi Kasus Pada PT. GMS - Jakarta
Market competition in food industry is growing tougher and tougher. More accurate quality service... more Market competition in food industry is growing tougher and tougher. More accurate quality service and faster delivery time are customer demands. One way to achieve them is to improve logistics and warehouse sector. Performance measurement must be established and monitored periodically. The research is conducted by using Balanced Scorecard at PT. GMS – Jakarta. The result has shown that three aspects: financial, customer, internal process must be maintained and one aspect must be improved: learning and growth
Analisis Jarak Tempuh dengan Menggunakan Sistem Simulasi
This research is designed to get the shortest time and distance for Order Picking activities. Thi... more This research is designed to get the shortest time and distance for Order Picking activities. This activity is categorized as a labor – intensive activity and is the most critical activity in warehouse operation. One way to achieve that is by using the routing method – S-Shape and Return Strategy which are the most common and widely used method by a picker (s). Congestion or queuing factor is included when there are more than one picker and simulated by Warehouse Real Time Simulator (WRTS) and to get the shortest distance by using Warehouse Optimizer (WO). By combining WRTS and WO, the result is shortest distance, shortest time, and optimal man power (picker).
Optimalisasi Tata Letak Gudang – Area Simpan: Studi Kasus di Pt.gms
Salah satu benefit dari tata letak yang optimal adalah bisa menghasilkan ruang yang tidak boros. ... more Salah satu benefit dari tata letak yang optimal adalah bisa menghasilkan ruang yang tidak boros. Penelitian yang dilakukan di PT.GMS dengan kondisi 24 lokasi simpan menghasilkan dimensi ruang simpan, panjang 4 m, lebar 12.6 m, lebar lorong 1.8 m, jumlah lorong 6 buah, dan produktivitas lorong sebesar 42.9%. Semakin banyak jumlah lokasi simpan, maka ruang simpan yang dibutuhkan akan semakin luas; dan semakin banyak jumlah lokasi simpan maka waktu untuk melakukan picking juga semakin bertambah. Kata Kunci: tata letak optimal, dimensi ruang
Peningkatan Efisiensi Picking Dengan Menggunakan Order Batching Statis – Earliest Due Date
Order Picking activity has about 55% of warehouse operational cost. Because of that, a company XY... more Order Picking activity has about 55% of warehouse operational cost. Because of that, a company XYZ, management views that warehouse activities which employs human energy need to be improved and be efficient. One of the strategies is to do order picking simultaneously for some customer orders, this way is common called Order Batching. The type of order batching is static and based on Earliest Due Date. The result of order batching implementation has an impact on reduction of travel distance about 31.8%.
Analisis Order Picking dengan Menggunakan Metode Routing Heuristics di Gudang PT. GMS
Order picking is the most labour and costly activities both in manual system and automated system... more Order picking is the most labour and costly activities both in manual system and automated system. So, it is necessary to improve efficiency and productivity. One way to do is to reduce travel distance or travel time. Time can be reduced by implementing routing heuristics method which has the shortest distance, and shorter distance means less energy consumption and fit to greener warehousing concept. The research at PT. GMS, Jakarta shows the routing method – Midpoint, The Largest Gap, and Combined – dynamic programming are the most efficient method
S-Metaheuristics Approach to Solve Traveling Salesman Problem
Metaheuristic algorithm is a state of the art optimization method which suitable for solving larg... more Metaheuristic algorithm is a state of the art optimization method which suitable for solving large and complex problem. Single solution technique – Smetaheuristic is one of metaheuristic algorithm that search near optimal solution and known as exploitation based. The research conducted to seek a better solution for deliverying goods to 29 destinations by comparing two well known optimization methods that can produce the shortest distance: Simulated Annealing (SA) and Tabu Search (TS). The result shows that TS – 107 KM has a shorter distance than SA – 119 KM. Exploration based method should be conducted for next research to produce information in which one is a better method
Penentuan dan Pengendalian Ruang Simpan Pendingin dan Hubungannya dengan Stok Pada Industri Makanan
Determining and controlling space area for freezer or chiller, several steps needed to calculate ... more Determining and controlling space area for freezer or chiller, several steps needed to calculate the following factors: unit of measurement, storage dimension, packaging dimension, minimum and maximum stock, and aisle allowance. Unit of measurement is used to convert inventory stock to physical inventory. Dimension is used to determine space area and stacks, include effective storage area and utilization. Minimum and maximum stock are used as indicator for monitoring current stock and to predict space area that will be used for some periods ahead. Aisle allowance is used for material and personnel movement. Next research needs to be developed for layout model to get the whole view of storage area.
There are two major optimization methods: Exact and Approximate methods. A well known exact metho... more There are two major optimization methods: Exact and Approximate methods. A well known exact method, Branch and Bound algorithm (B&B) and approximate methods, Elimination-based Fruit Fly Optimization Algorithm (EFOA) and Artificial Atom Algorithm (A3) are used for solving the Traveling Salesman Problem (TSP). For 56 destinations, the results of total distance, processing time, and the deviation between exact and approximate method will be compared where the distance between two destinations is a Euclidean distance and this study shows that the distance of B&B is 270, EFOA is 270 and A3 is 288.38 which deviates 6.81%. For time processing aspect, B&B needs 12.5 days to process, EFOA needs 36.59 seconds, A3 needs 35.34 seconds. But for 29 destinations, exact method is more powerful than approximate method.
There are two major optimization methods: Exact and Approximate methods. A well known exact metho... more There are two major optimization methods: Exact and Approximate methods. A well known exact method, Branch and Bound algorithm (B&B) and approximate methods, Elimination-based Fruit Fly Optimization Algorithm (EFOA) and Artificial Atom Algorithm (A3) are used for solving the Traveling Salesman Problem (TSP). For 56 destinations, the results of total distance, processing time, and the deviation between exact and approximate method will be compared where the distance between two destinations is a Euclidean distance and this study shows that the distance of B&B is 270 , EFOA is 270 and A3 is 288.38 which deviates 6.81%. For time processing aspect, B&B needs 12.5 days to process, EFOA needs 36.59 seconds, A3 needs 35.34 seconds. But for 29 destinations, exact method is more powerful than approximate method.
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