Design of self-regulating production control systems by tradeoffs programming

Self-regulating Production Control Systems (SPCSs) include production control systems such as kanban, buffered lines, base-stock, and their variations and combinations. In this work we develop and implement, for SPCS design, a new simulation-based optimization method called Tradeoffs Programming (TOP). TOP is a technique closely related to multi-objective dynamic programming that attempts to optimize inseparable problems. TOP is based on the idea that given correctly defined performance measures, many systems are nearly separable, and we can decompose the overall system using efficiency frontiers of simulated performance measures of the subsystems. We apply this technique to SPCS design and perform a number of experiments to validate and analyze our algorithm. We find TOP to be very accurate, extremely robust, and widely applicable.