Production scheduling optimisation with machine state and time-dependent energy costs

The increase of energy costs specially in manufacturing system encourages researchers to pay more attention to energy management in different ways. This paper investigates a non-preemptive single-machine manufacturing environment to reduce total energy costs of a production system. For this purpose, two new mathematical models are presented. The first contribution consists of an improvement of a mathematical formulation proposed in the literature which deals and deals with a scheduling problem at machine level to process the jobs in a predetermined order. The second model focuses on the generalisation of the previous one to deal simultaneously with the production scheduling at machine level as well as job level. So, the initial predetermined fixed sequence assumption is removed. Since this problem is NP-hard, an heuristic algorithm and a genetic algorithm based on the second model are developed to provide good solutions in reasonable computational time. Finally, the effectiveness of the proposed models and optimisation methods have been tested with different numerical experiments. In average, for small size instances which the mathematical model provides a solution in reasonable computational time, a gap of 2.2% for the heuristic and 1.82% for GA are achieved comparing to the exact method's solution. These results demonstrate the accuracy and efficiency of both proposed algorithms.