Product Variety Optimization: Simultaneous Optimization of Module Combination and Module Attributes

Abstract

Abstract This paper proposes a simultaneous optimization method for both module combination and module attributes of multiple products. As manufacturing competition has become restricted with high profitability and external constraints, simultaneous design of multiple products, which is called product variety design etc., becomes an important strategy. System-based optimal design paradigm is expected to be essential to rationalize such practices, since design for product variety is more complicated than one for a single product. Toward such a direction, we configure an optimization method for both module combination and module attributes across multiple products. The optimization method hybridizes a genetic algorithm, a mixed-integer programming method with a branch-and-bound technique, and a constrained nonlinear programming method, i.e., a successive quadratic programming method. In its optimization process, the first optimizes the combinatorial pattern of module commonality and similarity among different products, the second optimizes the directions of similarity on scale-based variety, and the third optimizes the continuous module attributes under the others. Finally it is applied to the simultaneous design problem of multiple airplanes to demonstrate its validity and effectiveness.

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