Solving The Problem Of Complex Parallel Machine Scheduling Based On Hybrid Discrete Particle Swarm Optimization

In recent years, non traditional scheduling problem, such as parallel machine scheduling problems, has become a hotspot in research of production scheduling problems. As a simply and effective intelligent algorithm, discrete partial swarm optimization algorithm (DPSO) has attracted much attention and gained successful applications in a variety of fields, such as mechanical processing and smelting iron and steel, For the particle swarm optimization algorithm used in parallel production scheduling problems has become the international frontier research topics. Thus, this disscertation aims at studying scheduling algorithms based on hybrid DPSO for two kinds of important production scheduling problems. The main work of this dissertation is summarized as follows:Firstly, after analyzing the structural properties of the parallel machine scheduling problems with multiple operations and process restraints under the makespan criterion, we design a position update formula of particle, and reasonably fusing it with DPSO to propose a improve DPSO(IDPSO). Simulation results and comparisons show the effectiveness of the proposed algorithm.Secondly, after analyzing the structural properties of the complex parallel machine scheduling problems with arrival times, multiple operations, process restraints, and sequence-dependent setup times under the makespan criterion, we extend the updating the position of a particle method to this problem and also join in an interchange and insert local search, and then we combine IDPSO with the local search to present an efficient hybrid DPSO. Simulation results and comparisons demonstrate the efficiency and robustness of the presented algorithm.Thirdly, after analyzing the secondly of the complex parallel machine scheduling problems under the makespan criterion, analying the inertia weight and study factor effect of DPSO algorithm to present an efficient adaptive DPSO algorithm and then we combine HDPSO form secondly to present an efficient adaptive hybrid discrete partial swarm optimization algorithm, The simulation experiment verifies the necessity and effectiveness of AHDPSO algorithm with adaptive.By the literature survey shows, discrete partial swarm optimization algorithm for parallel machine scheduling is very scarce. This paper discussed how to use mathematical model of scheduling problem of improved the existing DPSO algorithm, so the research has important academic and engineering.