A review of the current applications of genetic algorithms in mixed-model assembly line sequencing

Abstract

A mixed-model assembly line (MMAL) is a type of production line which is capable of producing a variety of different product models simultaneously and continuously. The design and planning of such assembly lines involves several long-and short-term problems. Among these problems, determining the sequence of products to be produced has received considerable attention from the researchers. This problem is known as the Mixed-Model Assembly Line Sequencing Problem (MMALSP). An important issue that complicates the sequencing problem is its combinatorial nature. Typically, an enormous number of possible production sequences exist, even for relatively small problems, so that finding the optimal solution is usually impractical. Due to the complexity of the problem, in recent years, a growing number of researchers have employed genetic algorithms (GAs). This paper reviews the genetic algorithm based MMAL sequencing approaches presented in the literature and provides two hierarchical classification schemes to classify academic efforts according to both specifications of MMALSP and specifications of GA-based approaches. Moreover, future research directions have been identified and are suggested.