Christian Böning and Henrik Prinzhorn and Eric C. Hund and Malte Stonis
A Memetic Algorithm for an EnergyCostsAware Flexible JobShop Scheduling Problem
1294 - 1307
2017
11
5
International Journal of Industrial and Manufacturing Engineering
https://publications.waset.org/pdf/10007514
https://publications.waset.org/vol/125
World Academy of Science, Engineering and Technology
In this article, the flexible jobshop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energycostsaware flexible jobshop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted.
Open Science Index 125, 2017