Parallel Hybrid Particle Swarm Optimization for Integration Framework of Optimal Operational Planning Problem of an Energy Plant and Production Scheduling Problem

Abstract

This paper proposes parallel hybrid particle swarm optimization (PHPSO) for the integration framework of optimal operational planning problem of an energy plant and production scheduling problem for actual reduction of the secondary energy costs in factories. Conventionally, fixed loads of the various tertiary energies have been utilized for solving optimal operational planning of the energy plant so far. On the contrary, in this paper, the loads of the various tertiary energies are calculated according to candidates of production scheduling and actual reduction of the secondary energy costs in factories is realized. The proposed method is applied to 10 jobs and 10 machines problem and it is verified that it can minimize the secondary energy cost and production time simultaneously with higher quality solutions compared with the conventional HPSO, and realize fast computation by parallel computation using PHPSO.