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Table 8: Impact of execution time adjustments Table 9 provides the total and individual costs of the best-found solution for each PTSPR.

Table 8 Impact of execution time adjustments Table 9 provides the total and individual costs of the best-found solution for each PTSPR.

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Table 2: Vehicle-based parameters
Table 2: Vehicle-based parameters
Table 3: Remaining model parameters
Table 3: Remaining model parameters
ere, we provide the necessary mathematical expressions to simplify the function which
ere, we provide the necessary mathematical expressions to simplify the function which
Figure 1: Proposed solution approach algorithmic approach is illustrated in Figure 1. che optimization of the route, while the second focuses on fuel-based decisions. The overal. The Nearest-Neighbor Heuristic (NNH) (Flood, 1956) is used to build an initial feasible
Figure 1: Proposed solution approach algorithmic approach is illustrated in Figure 1. che optimization of the route, while the second focuses on fuel-based decisions. The overal. The Nearest-Neighbor Heuristic (NNH) (Flood, 1956) is used to build an initial feasible
To provide clarity, a PTSPR solution is denoted as S = {RP, RS,SL}, where RP represents the speed levels for traversing the nodes within the integrated route. Specifically, with r
To provide clarity, a PTSPR solution is denoted as S = {RP, RS,SL}, where RP represents the speed levels for traversing the nodes within the integrated route. Specifically, with r
Figure 9: Contribution of local search operators und those derived from each operator or combination, considering all generated problen
Figure 9: Contribution of local search operators und those derived from each operator or combination, considering all generated problen
Table 5: TSP objective values due to different iteration limits of DB operator the improvement phase in this work is differentiated from the one considered in the work
Table 5: TSP objective values due to different iteration limits of DB operator the improvement phase in this work is differentiated from the one considered in the work
Table 6: Best found objective values using different shaking and search strategies the most efficient combinations of search and shaking strategies.
Table 6: Best found objective values using different shaking and search strategies the most efficient combinations of search and shaking strategies.
Table 7: PTSPR objective values method required 40.05s for the solution of the largest instance, while the second required it a valuable tool in addressing the computational complexities of the optimization problem
Table 7: PTSPR objective values method required 40.05s for the solution of the largest instance, while the second required it a valuable tool in addressing the computational complexities of the optimization problem
Table 9: Total and individual costs of the best-found solution 5.5. Sensitivity analysis The dimensions of the fuel tank and the refueling policy are recognized as two pivotal pa-
Table 9: Total and individual costs of the best-found solution 5.5. Sensitivity analysis The dimensions of the fuel tank and the refueling policy are recognized as two pivotal pa-
Table 10: Average values of the best-found total costs (€) for all PTSPR instances Table 11: Average values of the best-found refueling costs (€) for all PTSPR instances different combinations of fuel tank sizes and refueling policies.
Table 10: Average values of the best-found total costs (€) for all PTSPR instances Table 11: Average values of the best-found refueling costs (€) for all PTSPR instances different combinations of fuel tank sizes and refueling policies.
Table 12: Average values of the best-found emissions taxation costs (€) for all PTSPR instances
Table 12: Average values of the best-found emissions taxation costs (€) for all PTSPR instances
Table 13: Average values of the best-found driver wages costs (€) for all PTSPR instances Initially, it is noteworthy that the cost of refueling significantly contributes to the overall
Table 13: Average values of the best-found driver wages costs (€) for all PTSPR instances Initially, it is noteworthy that the cost of refueling significantly contributes to the overall
Table 14: Number of intermediate refueling stops for each problem case
Table 14: Number of intermediate refueling stops for each problem case
Table 15: Total refueling quantities for each problem case (in liters) tive scenarios. By investigating the impact of different fuel tank sizes and refueling policies
Table 15: Total refueling quantities for each problem case (in liters) tive scenarios. By investigating the impact of different fuel tank sizes and refueling policies
Table 16: Comparison between the proposed method and other solution approaches correspond to the best-found values.
Table 16: Comparison between the proposed method and other solution approaches correspond to the best-found values.
Table 16 — continued from previous page
Table 16 — continued from previous page
Related topics:
Metaheuristics (Operations Research)Variable Neighborhood SearchIntelligent OptimizationAdaptive Searching
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