Game-Based Hybrid Particle Swarm Optimization of Job-Shop Production Control

Abstract

The traditional multi-objective particle swarm optimization (PSO) cannot effectively handle the production control problem involving multiple types of production lines or production objectives. Therefore, this paper designs a game-based hybrid PSO (GBHPSO) for job-shop production control. Firstly, a job-shop model was established with parts processing line, parts assembly line, and product assembly line, and the production control ideas were designed to combine real-time monitoring of events and operation sequence adjustment. Then, the production control objectives were determined for the three production lines. After that, the GBHPSO was applied to solve the job-shop production control problem, the product utility function was constructed, and the execution low was detailed for the solving algorithm. Experiments demonstrate the effectiveness of our algorithm. The research provides a reference for applying our algorithm in resource allocation of other production fields.

Coupling of ODE and DES Models for Simulation of Air Defence in War-Gaming Experiment

“…In some aspects, the war-gaming is very close to civilian management and planning, e.g. logistics [2], job production [3] and uses established methods and algorithms such as route planning optimization [4].…”