Scheduling for a Container Supply Chain to Minimize Costs Using the Meta-Innovation Approach

Abstract

In this study, a problem of scheduling shipping lines for a container supply chain is addressed in order to minimize the costs of charging ships and the cost of maintaining the inventory of empty containers in the port by considering the time window of the port and the amount of fuel. This is a hard-NP problem and cannot be solved on a large scale with precise methods in a logical time. Therefore, to solve and optimize the model, a meta-innovative algorithm, a genetic algorithm, has been used. Also, to increase the effectiveness of the genetic algorithm, the parameters of the algorithm are adjusted using the Taguchi method. Finally, a number of problems have been solved to show the performance of this algorithm and its computational results have been compared with the results obtained from GAMS software. The study’s results demonstrate that the efficiency of displacement inside ports and fuel price on the overall costs, the optimal number of ships utilized, and the optimal scheduling table.