Solving a nonlinear side constrained transportation problem by using spanning tree-based genetic algorithm

The nonlinear side constraint transportation problem (NSCTP) arises when we want to find a reasonable assignment strategy to satisfy the source and destination requirement without shipping goods from sources to any pairs of prohibited destinations simultaneously so that the total cost can be minimized. With this side constraint, the difficulty of the problem increases significantly and it becomes impossible to solve it using conventional software packages such as LINDO. As there are exact methods to solve NSCTP in the literature, we propose a hybrid spanning tree-based genetic algorithm using Prufer number representation to solve it. In this method, we incorporate a fuzzy logic controller (FLC) to dynamically control the GA parameters. Comparisons with other conventional methods are presented and results show the proposed approach to be better as a whole