Simulated annealing based algorith for multiobjective fuzzy time-cost optimization problem

Time-cost trade off optimization problem is very important in both fields of construction management and combinatorial optimization. In this paper, we propose a Pareto approach to solve multi-objective time-cost optimization problem in a fuzzy environment. Activity duration and cost are represented by trapezoidal fuzzy numbers to assess the uncertainty associate with them. The objective considered is to minimize the project overall completion time and total project cost. An effective simulated annealing algorithm based on proposed approach is presented to solve multi-objective fuzzy time-cost optimization problem. An external memory of non-dominated solutions is considered to save and update the non-dominated solutions during the problem solving process. Numerical examples are used to evaluate and study the performance of the proposed algorithm.