Abstract
This paper analyzes a multi-product inbound lot-sizing and outbound dispatching problem with multi-vehicle types in a third-party logistics distribution center. The product must be delivered to the customers within the delivery time window and backlogging is not allowed. Replenishing orders are shipped by several types of vehicles with two types of the freight costs, i.e., uniform and decreasing, are considered. The objective of this study is to determine the lot-size and dispatching schedules to minimize the total cost with the sum of inbound and outbound transportation and inventory costs over the entire time horizon. In this study, we mathematically derive a mixed-integer programming model and propose a genetic algorithm (GA1) based on a local search heuristic algorithm to solve large-scale problems. In addition, we suggest a new genetic algorithm (GA2) with an adjusting algorithm to improve the performance of GA1. The basic mechanism of the GA2 is to provide an unidirectional partial move of products to available containers in the previous period. Finally, we analyze the results of GA1 and GA2 by evaluate the relative performance using the gap between the objective values of CPLEX and the each algorithm.
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