Using genetic algorithm and TOPSIS technique for multiobjective transportation problem: a hybrid approach

摘要

A hybrid approach to solve the multiobjective transportation problem (TP) is presented. The TP as a special type of the network optimization problems that has the special data structure in solution characterized as transportation graph. In encoding TP, we introduce a new chromosome's structure which is adopted as it is capable of representing all possible feasible solutions. Also, in order to keep the feasibility of the chromosome, the crossover and the mutation were modified. The proposed approach maintains a finite-sized archive of non-dominated solutions which gets iteratively updated in the presence of new solutions based on the concept of ε-dominance. Moreover, to help the decision maker to extract the best compromise solution from a finite set of alternatives, a technique for order performance by similarity to ideal solution (TOPSIS) method is adopted. Numerical simulations show the effectiveness and efficiency of the proposed approach.