D. Y. Sha

A hybrid particle swarm optimization for job shop scheduling problem

A hybrid particle swarm optimization (PSO) for the job shop problem (JSP) is proposed in this paper. In previous research, PSO particles search solutions in a continuous solution space. Since the solution space of the JSP is discrete, we modified the particle position representation, particle movement, and particle velocity to better suit PSO for the JSP. We modified the particle position based on preference list-based representation, particle movement based on swap operator, and particle velocity based on the tabu list concept in our algorithm. Giffler and Thompsons heuristic is used to decode a particle position into a schedule. Furthermore, we applied tabu search to improve the solution quality. The computational results show that the modified PSO performs better than the original design, and that the hybrid PSO is better than other traditional metaheuristics.

Supply chain network design: partner selection and production/distribution planning using a systematic model

In this paper, a novel multi-phase mathematical approach is presented for the design of a complex supply chain network. From the point of network design, customer demands, and for maximum overall utility, the important issues are to find suitable and quality companies, and to decide upon an appropriate production/distribution strategy. The proposed approach is based on the genetic algorithm (GA), the analytical hierarchy process (AHP), and the multi-attribute utility theory (MAUT) to satisfy simultaneously the preferences of the suppliers and the customers at each level in the network. A case study with a good quality solution is provided to confirm the efficiency and effectiveness of the proposed approach. Finally, to demonstrate the performance of the proposed approach, a comparative numerical experiment is performed by using the proposed approach and the common single-phase genetic algorithm (SGA). Empirical analysis results demonstrate that the proposed approach can outperform the SGA in partner selection and production/distribution planning for network design.

A dispatching rule for photolithography scheduling with an on-line rework strategy

Generally speaking, wafer fabrication factories define the photolithography area as the dispatching center of the entire factory. To establish a set of operative dispatching rules in the photolithography area while taking into consideration the rework of defective products would assist in coordinating and balancing the workload of the entire production line. Furthermore, it would help to enhance both the productivity and efficiency of the wafer fabrication, reduce the on-line WIP stock, shorten the production cycle time, and satisfy the requirements of customers regarding production due time and product quality. This research uses on-line rework as the basis for bringing the factor of reworking of a batch process into the dispatching rule for measurement. It then develops the dispatching rule (Rw-DR) which includes the rework strategy. In addition, this research focuses on the batch with high finished proportion in the photolithography area for finding a way to complete the manufacturing procedure faster, lighten the machine workload of the waiting line, and at the same time increase the output quantity.

A multi-criterion interaction-oriented model with proportional rule for designing supply chain networks

Supply chain management has offered a way to improve the industrial environment becomes more competitive. While, the commonly seen methodologies may be effective in solving the production-distribution problem only from supplier- or customer-oriented consideration, those cannot present the interactive relationship between upstream and downstream enterprises. In the competitive semiconductor industry environment, considering the viewpoints of the supplier and consumer simultaneously is particularly required, because multiple manufacturing and demanding steps are performed at separate situations, concurrently. In this paper, we propose an interaction-oriented approach, which bases on the analytic hierarchy process (AHP) methodology and proportional rule, to solve the semiconductor distribution problem with multiple quantitative and qualitative criteria. The developed approach gives an expected satisfaction for the all participators of the whole chain while the cooperative information is shared perfectly and effectively. Analysis results demonstrate the proposed methodology is efficient and effective through a real world case study.