DEVELOPING NEW CHARGED SYSTEM SEARCH-BASED ALGORITHM: APPLICATION IN THE TIME-COST TRADE-OFF PROBLEMS

Abstract

The trade-off between the total cost and project duration is one of the most important parameters of construction project planning. There are various methods to optimize time-cost trade-off problems. Mathematical programming models as one type of them cannot solve large and complex networks effectively. On the other hand, although the meta-heuristics algorithms in many cases can find a complete set of solutions but to optimize the time-cost trade-off problems in very massive construction projects they need to spend a lot of time, so existence a powerful algorithm with higher convergence rate is necessary. In this paper new procedures MAWA-CSS and SMOCSS are introduced to generalize the well-known CSS algorithm for solving TCTP optimization problem and all multi-objective optimization problems in discrete and continuous search space. The overall structure of SMOCSS algorithm is similar to the MOPSO and to determine the Charge magnitude of particles a new simple method is introduced. The proposed method is examined for different test functions and the results are compared to the results of two well-known multi- objective algorithms (NSGA-II and MOPSO). In addition, two example of time-cost optimization problem (Feng and Zheng network with 18 and 7 activities respectively) are used to evaluate the performance of the proposed algorithms. The results indicate that the SMOCSS algorithm has the ability to find out the optimal solution and define the Pareto front as well in reasonable time. Hence the proposed approach in this paper is much adaptive and suitable for tackling TCTP, which is useful and beneficial for decision-making on the trade-off between project duration and total cost.