Colony Location Algorithm for multiobjective assignment problem with application to e-Brokerage

Trade matching problem of e-Brokerage can be described by a multiobjective assignment model. To solve the problem, we propose a novel artificial-life based algorithm, Colony Location Algorithm (CLA). It mimics the growth process with resource competition. By using fertilization operation, the growth of the colonies located at right fields can be encouraged. Thus, the optimal solution can be found when the colonies all locate on the right fields. The computational example from an experimental website of e-brokerage has proven that CLS can achieve a Pareto optimal solution without the information of the preference structure of decision makers. It provides an alternative method for multiobjective optimization problems.