Two-stage assembly scheduling problem for processing products with dynamic component-sizes and a setup time

Abstract

In this paper, two-stage assembly flow shop scheduling problem (TSAFSP) to assemble products having dynamic component-sizes is considered. In the machining stage, a single machining machine produces various types of components to assemble the products. During the machining process, a setup time is required whenever the machining machine starts to process a new component or processes a different component. When the required components are available for the associated product from the machining stage, a single assembly machine can assemble these components into the product in the assembly stage. To solve the problem, a novel mixed integer linear programming model is derived. Three genetic algorithms (GAs) with different chromosome representations are proposed due to the intractability of the optimal solution for large-sized problems. One GA has a chromosome to represent a complete solution. Two hybrid genetic algorithms (HGAs) have a simple chromosome to represent a partial solution, and the rest of the solution is provided by an effective local search heuristic given the partial solution. The performance of the GAs is compared by using randomly generated examples.