Solving the Distributed Two Machine Flow-Shop Scheduling Problem Using Differential Evolution
Flow-shop scheduling covers a class of widely studied optimisation problem which focus on optimally sequencing a set of jobs to be processed on a set of machines according to a given set of constraints. Recently, greater research attention has been given to distributed variants of this problem. Here we concentrate on the distributed two machine flow-shop scheduling problem (DTMFSP), a special case of classic two machine flow-shop scheduling, with the overall goal of minimising makespan. We apply Differential Evolution to solve the DTMFSP, presenting new best-known results for some benchmark instances from the literature. A comparison to previous approaches from the literature based on the Harmony Search algorithm is also given.
- 2.Deng, J., Wang, L., Shen, J., Zheng, X.: An improved harmony search algorithm for the distributed two machine flow-shop scheduling problem. In: Kim, J.H., Geem, Z.W. (eds.) Harmony Search Algorithm. AISC, vol. 382, pp. 97–108. Springer, Heidelberg (2016). doi: 10.1007/978-3-662-47926-1_11 CrossRefGoogle Scholar
- 5.Lin, B.M., Hwang, F., Gupta, J.N.: Two-machine flowshop scheduling with three-operation jobs subject to a fixed job sequence. J. Sched., 1–10 (2017, to appear)Google Scholar
- 10.Tanabe, R., Fukunaga, A.: Success-history based parameter adaptation for differential evolution. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2013), pp. 71–78. IEEE (2013)Google Scholar