Mousa, A., Geneedy, H., Elmekawy, A. (2010). Efficient Evolutionary Algorithm for solving Multiobjective Transportation Problem. The International Conference on Mathematics and Engineering Physics, 5(International Conference on Mathematics and Engineering Physics (ICMEP-5)), 1-11. doi: 10.21608/icmep.2010.29806

A. A. Mousa; Hamdy M. Geneedy; Adel Y. Elmekawy. "Efficient Evolutionary Algorithm for solving Multiobjective Transportation Problem". The International Conference on Mathematics and Engineering Physics, 5, International Conference on Mathematics and Engineering Physics (ICMEP-5), 2010, 1-11. doi: 10.21608/icmep.2010.29806

Mousa, A., Geneedy, H., Elmekawy, A. (2010). 'Efficient Evolutionary Algorithm for solving Multiobjective Transportation Problem', The International Conference on Mathematics and Engineering Physics, 5(International Conference on Mathematics and Engineering Physics (ICMEP-5)), pp. 1-11. doi: 10.21608/icmep.2010.29806

Mousa, A., Geneedy, H., Elmekawy, A. Efficient Evolutionary Algorithm for solving Multiobjective Transportation Problem. The International Conference on Mathematics and Engineering Physics, 2010; 5(International Conference on Mathematics and Engineering Physics (ICMEP-5)): 1-11. doi: 10.21608/icmep.2010.29806

Efficient Evolutionary Algorithm for solving Multiobjective Transportation Problem

Abstract This paper presents an efficient evolutionary algorithm for solving multiobjective transportation problem MOTP. a new chromosome's structure was introduced, which is adopted as it is capable to representing all possible feasible solutions. Also, in order to keep the feasibility of the chromosome, a criterion of the feasibility was designed. Based on this criterion the crossover and mutation were implemented and they can always generate feasible chromosomes. To avoid an overwhelming number of solutions the algorithm maintains a finite-sized archive of non-dominated solutions, which gets iteratively updated in the presence of new solutions based on the concept of Epsilon-dominance. Epsilon dominance process saves the most representative solutions. Finally, we report numerical results in order to establish the actual computational burden of the proposed algorithm and to assess its performances with respect to classical approaches for solving MOTP.