| Summary: | 碩士 === 輔仁大學 === 企業管理學系管理學碩士班 === 99 === In the current competitive market environment and due to the popularity of the just-in-time philosophy nowadays, if enterprises want to reduce inventory cost and satisfy costumer at the same time, they must provide diverse products or services with limited resources, and accomplish works during the specified period of time called “ due window ”. Therefore, scheduling plays a crucial role in manufacturing and service industries. In recent years, the flow shop with multiprocessors environment (FSMP) is often applied to practice industry. So this study chooses FSMP scheduling problem which has multi-objective and due window as the object of study.
For this kind of scheduling problem, most scholars use heuristic solution methods to solve it. In most of these methods, particle swarm optimization (PSO) has been proven to be an effective and efficient tool in some engineering fields such as data clustering, financial forecasting, image processing, and etc. However, PSO was seldom applied in the aspect of scheduling researches, compared with those historical methods such as genetic algorithms (GA) and ant colony optimization (ACO). This study will be based on the concept of PSO, develop a modified PSO called “ adaptive particle swarm optimization ” (APSO). This study also compares the results of its operations with integer programming and the three inertia PSO approaches. The experiment confirmed that all PSO approaches are able to obtain approximate optimal solution in a short time for solving small scale FSMP scheduling problems. APSO has about 50.56 %, 29.93% and 15.08% increment of effectively contrasted to the three inertia PSO. In testing of large scale FSMP scheduling problems, integer programming is not able to get a optimal solution in the reasonable time, so the study cannot calculate APSO's increment of effectively contrasted to each three inertia PSO. But by the statistical test, it elucidated that APSO is a superior method which has a better solving efficient than others.
|
|---|
