Special Issue on Production Planning and Scheduling

抄録

This issue focuses on production planning and scheduling for production system and the related problems that have arisen in these areas in the last half century as digital computer systems developed. These problems relate to production management, production planning, shop floor control, product design and process planning. In the first stage of production planning and scheduling systems R&D, optimization is a key issue that has been widely discussed and many theories and optimization algorithms proposed. Rule-based methods are discussed as potential solutions to these problems.

With rapid advances in computer and information processing technologies and performance, tremendous progress has been made in the areas of production systems such as production planning, production scheduling, advances production systems (APS), enterprise resource planning (ERP), just-in time (JIT) processes, the theory of constraint (TOC), product data management (PDM) and computer-aided design / manufacturing / engineering (CAD/CAM/CAE).

With new approaches being proposed and applied all the time to the production planning and scheduling problems to cope with dynamically changing manufacturing environments, manufacturers must respond quickly and flexibly to customer needs and requests in domestic and international markets under globalized competition. These include metaheuristics, multiagent approaches, object-oriented modeling, and large-scale simulation/evaluation.

This special issue addresses the latest research advances, applications, and case studies in production planning and scheduling covering such as decentralized and autonomous production systems, distributed simulation models, robust capacity planning models, wireless sensor networks for production systems and applications to automotive component and steel production.

We hope that learning about these advances will enable readers to share their own experience and knowledge in technology, new developments and the potential applications of production planning and scheduling methods and solutions.