Scheduling on a two-machine permutation flow shop under time-of-use electricity tariffs

Shijin Wang (1) , Zhanguo Zhu (2) , Kan Fang , Feng Chu (3) , Chengbin Chu (4)

1 Department of Management Science and Engineering
2 College of Economics and Management
3 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
4 ESIEE Paris

We consider a two-machine permutation flow shop scheduling problem to minimise the total electricity cost of processing jobs under time-of-use electricity tariffs. We formulate the problem as a mixed integer linear programming, then we design two heuristic algorithms based on Johnson’s rule and dynamic programming method, respectively. In particular, we show how to find an optimal schedule using dynamic programming when the processing sequence is fixed. In addition, we propose an iterated local search algorithm to solve the problem with problem-tailored procedures and move operators, and test the computational performance of these methods on randomly generated instances.

Keywords: scheduling; flow shop; electricity cost; dynamic programming; iterated local search

Domains: Operations Research [math.OC]

Shijin Wang, Zhanguo Zhu, Kan Fang, Feng Chu, Chengbin Chu. Scheduling on a two-machine permutation flow shop under time-of-use electricity tariffs. International Journal of Production Research, 2018, 56 (9), pp.3173--3187. ⟨10.1080/00207543.2017.1401236⟩. ⟨hal-01690495⟩