A genetic algorithm using priority-based encoding with new operators for fixed charge transportation problems

In this paper, we propose a genetic algorithm using priority-based encoding (pb-GA) for linear and nonlinear fixed charge transportation problems (fcTP) in which new operators for more exploration are proposed. We modify a priority-based decoding procedure proposed by Gen et al. [1] to adapt with the fcTP structure. After comparing well-known representation methods for a transportation problem, we explain our proposed pb-GA. We compare the performance of the pb-GA with the recently used spanning tree-based genetic algorithm (st-GA) using numerous examples of linear and nonlinear fcTPs. Finally, computational results show that the proposed pb-GA gives better results than the st-GA both in terms of the solution quality and computation time, especially for medium- and large-sized problems. Numerical experiments show that the proposed pb-GA better absorbs the characteristics of the nonlinear fcTPs.

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► Considering linear and nonlinear fixed charge transportation problems (fcTPs).
► Proposing a genetic algorithm using priority-based encoding (pb-GA) for fcTPs.
► Modifying a priority-based decoding procedure to adapt with the fcTP structure.
► Proposing two new crossover operators (OPEX and PEX) and new mutation operator (OPEX) based on two-partite chromosomes in the priority-based encoding.
► Comparing the performance of the pb-GA with the recently used spanning tree-based genetic algorithm (st-GA).