Minimizing total flow time on a batch processing machine using a hybrid max–min ant system - Rafiee Parsa, N.; Karimi, B.; Moattar Husseini, S.M. (Computers & industrial engineering, 2016)
•The problem of minimizing total flow time on a single batch processing machine with non-identical job sizes is addressed.•A binary mixed integer programming model is formulated.•An effective hybrid max–min ant system is proposed.•The effectiveness of the proposed approach is evaluated using randomly generated test instances. A single batch processing machine scheduling problem with non-identical job sizes to minimize the total flow time is investigated. The problem is formulated as a binary mixed integer programming model. Since the research problem is shown to be NP-hard, a hybrid metaheuristic algorithm based on the max–min ant system (MMAS) is proposed. MMAS is an ant colony optimization algorithm derived from ant system. In the proposed algorithm, first, a sequence of jobs is constructed based on the MMAS algorithm. Then, a dynamic programming algorithm is applied to obtain the optimal batching for the given job sequence. At last, an effective local search procedure is embedded in the algorithm for finding higher quality solutions. The performance of the proposed algorithm is compared with CPLEX and available heuristics in the literature. Computational results demonstrate the efficacy of the proposed algorithm in terms of the solution quality.