Algoritmo voraz iterativo con multivecindad aplicado al problema de secuenciación difuso multiproducto y multietapas

Abstract

This work explored the Fuzzy Multiproduct Multistage Scheduling Problem (FMMSP) that can be observed in industries without an establishedstandardization. This problem has already been treated with four algorithms (DBSA-LS, BDBSA, MBSA, and IGA), but all of them present variability en the solution they find, and some of them present solutions of lesser quality. Here the Multi-Neighborhood Iterated Greedy algorithm (MNIG) was adapted to solve the FMMSP model, and it was found that the MNIG algorithm gives solutions of high quality and with less variability than the other four algorithms. The results from applying the algorithm to an instance of the problem (the o10s2u5 instance, which is the only public instance of this problem), will be reported, and the results will be compared with those of the other four algorithms DBSA-LS, BDBSA, MBSA, and IGA. The execution time will also be measured, which was not measured for the other four algorithms. The MNIG algorithm will also be applied to Taillard’s instances, these are instances of the basic flow shop problem.