A heuristic genetic algorithm for subcontractor selection in a global manufacturing environment

Presents an investigation of how partner selection problems may be optimized by the use of a precedence network of subprojects. At the start, the problem is described by a model with the subscript type of variables and a non-analytical objective function. It cannot be solved by general mathematical programming methods. By using the fuzzy rule quantification method, a fuzzy logic-based decision-making approach for the project scheduling is proposed. We then develop a fuzzy decision embedded heuristic genetic algorithm (GA/FD) to find the solution for partner selection. The approach was demonstrated by the use of an experimental example drawn from a coal-fired power station construction project. The results show us that the suggested approach can quickly achieve the optimal solution for large-sized problems.