Single-machine batch scheduling under time-of-use tariffs: New mixed-integer programming approaches

Junheng Cheng (1, 2) , Feng Chu (1, 3) , Ming Liu (4) , Weili Xia (2)

1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
2 School of Management
3 School of Construction and Management Engineering
4 School of Economics and Management

Time-of-use (TOU) pricing has been implemented by many electricity suppliers to alleviate the peak load of power grid, which provides a good opportunity for industrial consumers to reduce their energy bills. In industrial enterprises that involve batch processing machines, energy expenditure often accounts for large portion of the final product cost. Optimizing batch scheduling under TOU tariffs in these enterprises will be of great significance. This study investigates a single machine batch scheduling problem under TOU tariffs. The objective is to minimize the total electricity cost by optimally scheduling all jobs within a given planning horizon. Two mixed integer linear programming (MILP) models, which are respectively based on time-index formulation and time-interval formulation, are developed for the problem. The models are solved by CPLEX. Computational results on randomly generated instances demonstrate the effectiveness of the proposed approaches.

Domaines: Recherche opérationnelle [math.OC]

Junheng Cheng, Feng Chu, Ming Liu, Weili Xia. Single-machine batch scheduling under time-of-use tariffs: New mixed-integer programming approaches. 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016), Oct 2016, Budapest, Hungary. pp.3498--3503, ⟨10.1109/SMC.2016.7844775⟩. ⟨hal-01502799⟩