A memetic algorithm to solve uncertain energy-efficient flow shop scheduling problems

摘要

This paper addresses energy-efficient flow shop scheduling problems with uncertainties such as cancelled and new orders to minimize the total energy cost (TEC). The absenteeism of workers is also considered. As this problem is NP-hard (non-deterministic polynomial-time hard) in nature, an improved memetic algorithm (IMA) is proposed to tackle this problem. A constructive heuristic is built-in with the memetic algorithm (MA) for the improvement of the solution quality. Additionally, likelihood-based selection, crossover, and mutation operators are utilized in the IMA. A variable neighborhood search (VNS) algorithm is also hybridized as a local exploration heuristics. Broad computational experimentations are presented. The results of IMA are compared with a set of algorithms addressed in the literature. It is shown that the IMA overtakes other algorithms in terms of solution quality.