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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Chakir Tajani
Abdelmalek Essaadi University
Computer Science & IT Electrical & Electronics Engineering

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HOPX Crossover Operator for the Fixed Charge Logistic Model with Priority Based Encoding Ahmed Lahjouji El Idrissi; Chakir Tajani; Mohamed Sabbane
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (446.914 KB) | DOI: 10.11591/ijece.v8i6.pp5351-5358

Abstract

In this paper, we are interested to an important Logistic problem modelised us optimization problem. It is the fixed charge transportation problem (FCTP) where the aim is to find the optimal solution which minimizes the objective function containig two costs, variable costs proportional to the amount shipped and fixed cost regardless of the quantity transported. To solve this kind of problem, metaheuristics and evolutionary methods should be applied. Genetic algorithms (GAs) seem to be one of such hopeful approaches which is based both on probability operators (Crossover and mutation) responsible for widen the solution space. The different characteristics of those operators influence on the performance and the quality of the genetic algorithm. In order to improve the performance of the GA to solve the FCTP, we propose a new adapted crossover operator called HOPX with the priority-based encoding by hybridizing the characteristics of the two most performent operators, the Order Crossover (OX) and Position-based crossover (PX). Numerical results are presented and discussed for several instances showing the performance of the developed approach to obtain optimal solution in reduced time in comparison to GAs with other crossover operators.
Genetic algorithm with immigration strategy to solve the fixed charge transportation problem Ahmed Lahjouji El Idrissi; Chakir Tajani
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp313-320

Abstract

This paper is about improving the performance of genetic algorithm (GA) to solve the fixed-charge transportation problem (FCTP). Several approaches have been developed, based on adaptation and improvement of genetic operators. We propose a new genetic algorithm adopting an immigration strategy to maintain the diversity in the population and then overcome the stagnation of the values of the objective function. Thereby, we applied two types of immigration, random immigration and memory-based immigration. The numerical results obtained with several standard instances of the FCTP problem demonstrate the effectiveness of these strategies in improving the performance of the GA. Especilly, for the second strategy.
Co-Authors Ahmed Lahjouji El Idrissi Ahmed Lahjouji El Idrissi Mohamed Sabbane