Abstract

This paper describes the effects of chromosome length for solving maritime inventory routing problems (MIRP) by using a hyper-heuristics based Genetic Algorithm (GA). The approach uses a set of heuristic combinations, each of which consist of strategies that correspond to a ship assignment. These strategies are represented by a chromosome that may have several assignments. We examine several number of chromosome length to encourage the evolution of good heuristics combinations. Moreover, a variation of several number chromosome length is necessary since we do not know in advance how many ship assignments are needed to cover demands during a predefined planning horizon. At every iteration a number of chromosomes are evaluated and evolved within a GA framework. In this study, the approach has been applied on several test cases for transporting multiple oil products from a production facility to some consumption ports, by using several heterogeneous ships with undedicated compartments. The results show that a hyper-heuristics based GA reaches the same global optimal as the solutions in the mathematical model, but with a significant decrease in computational time. Moreover, the use two numbers of chromosome length proves that three assignments in one step (3AiOS) mostly got better solutions and lower minimum total number of assignments than the two assignments (2AiOS).

Original languageEnglish
Pages (from-to)1733-1741
Number of pages9
JournalProceedings of the International Conference on Industrial Engineering and Operations Management
Volume2019
Issue numberMAR
Publication statusPublished - 2019
Event9th International Conference on Industrial Engineering and Operations Management, IEOM 2019 - Bangkok, Thailand
Duration: 5 Mar 20197 Mar 2019

Keywords

  • Chromosome Lenght
  • Genetic Algorithm
  • Hyper-heuristics
  • Inventory Routing Problem
  • Maritime Transportation

Fingerprint

Dive into the research topics of 'The effects of chromosome length on hyper-heuristics for solving the maritime inventory routing problems'. Together they form a unique fingerprint.

Cite this