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A knowledge-based system for solving multi-objective assembly line balancing problems
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DOI：10.1080/00207549608905043.png)
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Abstract
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This paper presents design-and-development details of a knowledge-based system that solve multi-objective assembly line balancing problems to obtain an optimal assignment of a set of assembly tasks to a sequence of workstations. Assembly line balancing problems arise in high-volume production systems with a significant regularity. The formulation and solutions currently employed by managers and practitioners usually aims at optimizing one objective (e.g., number of work stations or cycle time), thus ignoring the multi-dimensional nature of the overall objectives of the manager. Furthermore, in practice ALBPs are ill-defined and ill-structured, making it difficult to formulate and solve them by mere mathematical approaches. The knowledge-based system multi-objective assembly line balancing approach, presented in this paper, addresses these needs. This paper presents a knowledge-base multi-objective approach to assembly line balancing problems. It demonstrates how such a system can be constructed and how a variety of assembly line balancing methods can be used in a uniform structure to support the decision maker (DM) to formulate, validate the formulation, generate alternatives, and choose the best alternative. Its capabilities include: (1) Elimination of inconsistencies in the problem structure, (2) The use of multi-objective formulation of the problem, (3) A well-designed user-interface, (4) Pursuance of the overall objectives of the manager via a new mechanism, (5) Development of several efficient alternatives, consistent with the user-specified constraint structure, providing the decision maker with a larger number of choices, and, (6) An approach for ranking and prioritizing alternatives consistent with the decision-maker's preferences.
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