Discrete Time-Cost Tradeoff with a Novel Hybrid Meta-Heuristic

In this paper, we present a new hybrid meta-heuristic (HMH) technique for solving multiobjective discrete time-cost tradeoff (TCT) problem in project scheduling. The proposed technique hybridizes a multiobjective genetic algorithm and simulated annealing, and is apposite for problems where generation of complete Pareto front, a TCT curve in this case, is essential for a decision-maker. Discrete TCT problem is known to be NP-hard. We solved two test problems of discrete TCT using HMH – on comparing the Pareto front results of HMH with those of analytical method, HMH performs well in terms of efficiency and accuracy.

[1]  Chung-Wei Feng,et al.  Using genetic algorithms to solve construction time-cost trade-off problems , 1997 .

[2]  Sanjay Srivastava,et al.  Multi-resource-constrained discrete time-cost tradeoff with MOGA based hybrid method , 2007, 2007 IEEE Congress on Evolutionary Computation.

[3]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[4]  Ali M. S. Zalzala,et al.  Recent developments in evolutionary computation for manufacturing optimization: problems, solutions, and comparisons , 2000, IEEE Trans. Evol. Comput..

[5]  Prabuddha De,et al.  Complexity of the Discrete Time-Cost Tradeoff Problem for Project Networks , 1997, Oper. Res..

[6]  Carlos A. Coello Coello,et al.  Asymptotic convergence of metaheuristics for multiobjective optimization problems , 2006, Soft Comput..

[7]  Sou-Sen Leu,et al.  GA-BASED MULTICRITERIA OPTIMAL MODEL FOR CONSTRUCTION SCHEDULING , 1999 .

[8]  Mario Vanhoucke.  New computational results for the discrete time/cost trade-off problem with time-switch constraints , 2005 .

[9]  Sanjay Srivastava,et al.  MOGA-based time-cost tradeoffs: Responsiveness for project uncertainties , 2007, 2007 IEEE Congress on Evolutionary Computation.

[10]  M. Vanhoucke,et al.  THE DISCRETE TIME/COST TRADE-OFF PROBLEM UNDER VARIOUS ASSUMPTIONS EXACT AND HEURISTIC PROCEDURES , 2005 .

[11]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[12]  Prabuddha De,et al.  The discrete time-cost tradeoff problem revisited , 1995 .

[13]  Yoh-Han Pao,et al.  Combinatorial optimization with use of guided evolutionary simulated annealing , 1995, IEEE Trans. Neural Networks.

[14]  Xavier Gandibleux,et al.  A survey and annotated bibliography of multiobjective combinatorial optimization , 2000, OR Spectr..