An Ant Colony Optimisation algorithm for partner selection in Virtual Enterprises

Partner selection problem seeks to find a best combination of enterprises by optimising a nonlinear objective over the given constraints. In this paper the partner selection problem is modelled as a nonlinear integer programming problem and an Ant Colony Optimisation (ACO) algorithm embedded project scheduling is presented for solving the problem with the lead time, subproject cost and risk factor constraints in Virtual Enterprises (VE). Genetic Algorithm (GA) and enumeration algorithm are introduced for comparison to check the effectiveness of the ACO algorithm. A case study is implemented to verify the feasibility of the proposed approach and the computational results are satisfactory.