A New Sequence Evolution Approach to Assembly Planning

Abstract

Assembly planning is the problem of finding the best or optimal sequence to assemble a product, starting from its design data. It is still solved manually in most advanced assembly plants, despite the large amount of related research. One of the main reasons might be the use of exact- and/or linear-solution approaches. This paper introduces a different approach by applying a modified genetic algorithm (GA). A “best” solution is generated without searching the complete candidate space, while search is performed on a sequence population basis. The GA is modified to cope with sequence nonlinearity and constraints. [S1087-1357(00)70401-1]