Solving multi-product inventory ship routing with a heterogeneous fleet model using a hybrid cross entropy-genetic algorithm: a case study in Indonesia

Abstract

This paper presents a model and an algorithm for an inventory ship routing problem (ISRP). It consists of two main parts: a model development of the ship routing problem in a multi-product inventory with a heterogeneous fleet and an algorithm development to solve the problem. The problem is referred to as ISRP. ISRP considers several parameters including the deadweight tonnage (DWT), product compatibility, port setup, and compartment washing costs. Considering these parameters, the objective function is to minimize the total cost, which consists of traveling, port setup, ship charter, and compartment washing costs. From the resulting model, there are two major steps used to solve the problem. The first is to select the ships in order to satisfy the constraint that restricts the mooring rule. The second is to find the best route, product allocation, and shipped quantity. ISRP is an Non Polynomial-hard problem. Finding the solution of such problem needs a high computation time. A new hybrid metaheuristics, namely the cross entropy-genetic algorithm (CEGA), was proposed to solve ISRP. The results were then compared with those resulted from a hybrid Tabu Search to measure the hybrid CEGA performance. The results showed that CEGA provided better solutions than those produced by the hybrid Tabu Search.

Keywords

• Heterogeneous fleet
• cross entropy
• genetic algorithm
• multi-product
• metaheuristics
• inventory ship routing problem