Energy-efficient job shop scheduling problem using an improved particle swarm algorithm

To deal with the fastly increasing energy consumption and energy costs in the manufacturing process, manufacturing companies are forced to search some methods to reduce energy cost without affecting the yield of their products or sacrificing quality. In this paper, an extended job shop scheduling problem, where machines can work at different speeds with different energy consumption, is modified. A serial of analytical functions are developed to denote the relationship between Energy-efficiency and Makespan. And a improved particle swarm algorithm, inspired by the hormone mechanism, is developed to solve the energy-efficient job shop scheduling problem. In term of practical application aspect, the result from computational experiments indicate that durations of processing periods and processing speed of machines have great effect on energy-efficiency scheduling solution, and our algorithm could solve instances with a good solution quality.