Two hybrid meta-heuristics for the finite horizon ELSP in flexible flow lines with unrelated parallel machines

This article addresses the economic lot sizing and scheduling problem in flexible flow lines with unrelated parallel machines over a finite planning horizon. The objective is determination of a cyclic schedule that minimizes the sum of setup and inventory holding costs per unit time without any stock-out. A new mixed zero–one nonlinear mathematical programming has been developed for the problem. Due to difficulty of obtaining the optimal solution especially for medium and large-sized problems, we have also proposed two algorithms: a hybrid genetic algorithm (HGA) and a simulated annealing (SA). Two efficient constructive heuristic algorithms have been also proposed that provide some initial solutions for the algorithms. Moreover, a new local search approach has been proposed to improve solution quality of algorithms. The two proposed solution methods are compared on 180 randomly generated problems. Computational results indicate the superiority of the proposed HGA in compare to the SA with respect to the solution quality, but the proposed SA outperforms the proposed HGA with respect to the required computations time.