Genetic Algorithm Based Hybrid Approach to solve Multi-objective Interval Transportation Problem
In this work, we determine the best effective solution of multi-objective interval transportation problem (MOITP) with genetic algorithm (GA) based hybrid approach. Taking the different cases involve shape parameter and aspiration level in exponential membership
function, the higher degree of satisfaction can be obtained. Moreover, it provides to decision maker (DM) several different choices to acquire a protable decision in their area. Proposed work optimize more than one objective functions by taking the highest degree of
satisfaction. Moreover, the objective function corresponding to the problem in this paper are non-commensurable, additionally and they coflict with one another. With realistic circumstances, a numerical instance is supplied with a statistic set to check the eectiveness
of the projected GA approach.
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