A two-phase metaheuristic approach for solving Economic Lot Scheduling Problems

In this paper, economic lot scheduling problem is investigated using time-varying lot sizes approach. The process of finding the best production sequence consists of two-phase implementation of metaheuristics. In the first phase, we propose a genetic algorithm that makes use of the proposed new lower bound to arrive at the good set of production frequencies of products for ELSP without/with backorders. In the second phase, the best sequence of part production is achieved by using the above set of frequencies and employing a GA and an ant-colony algorithm. Computational experiments reveal the effectiveness of the two-phase approach over the conventional single-phase approach.