Hybrid Metaheuristic for Solving Maritime Inventory Routing Problem in Bulk Product Transportation

Abstract

Maritime Inventory Routing Problem (MIRP) is an important issue in the optimization of maritime distribution and transportation. This problem is related to planned ship's routing and scheduling in delivery of goods from the depot to some demand points by minimizing associated costs such as transportation and inventory management costs. This paper discusses how to solve MIRP with multi ships and limited undedicated compartments used to deliver bulk products from the depot port to the several consumption ports. The new hybrid metaheuristics are used to find the optimal assignment routes and schedule of ships along time horizon. This research modifies several metaheuristics algorithms called Modified Hybrid Particle Swarm Optimization (MHPSO) to find the best solution for MIRP. The algorithm of this method is developed from the combination of Particle Swarm Optimization (PSO), Nahwaz-Enscore-Ham (NEH), and 3-Opt. Some metaheuristic methods such as Genetic Algorithm (GA), Tabu Search (TS), Particle Swarm Optimization (PSO), Hybrid Genetic Algorithm (HGA), and Hybrid Tabu Search (HTS) were also developed in the same way to test and compare with the proposed method. Based on the ten test data instances, it can be concluded that MHPSO provides 0.64% effectiveness better results than other metaheuristic methods.