A hybrid knowledge based/optimization system for automated selection of materials handling system

Abstract

An efficient materials handling system (MHS) to transport products between processing centres greatly improve the competitiveness of a product through a reduction of handling cost. This paper proposes a new methodology for automating the determination of a materials handling system by combining knowledge-based and optimization approaches. The proposed system selects the optimum combining knowledge-based and optimization approaches. The proposed system selects the optimum materials handling equipment and the assignment of moves, extending previous concepts in analytical methods and expert systems. The optimization model considers minimization of both the cost and total aisle space requirement as objectives. The knowledge base consists of rules to determine feasibility of using particular materials handling equipment for a given move. The methodology employs the “systems approach” in selecting the optimum MHS for a given set of moves while considering many practical aspects associated with the MHS selection problem. The application of the methodology is demonstrated with an example problem involving 112 moves.