Using Elitist Particle Swarm Optimization to Facilitate Bicriterion Time-Cost Trade-Off Analysis |
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Authors: | I-Tung Yang |
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Affiliation: | Assistant Professor, Dept. of Construction Engineering, National Taiwan Univ. of Science and Technology, No. 43, Section 4, Keelung Rd., Taipei 106, Taiwan. E-mail: ityang@mail.ntust.edu.tw
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Abstract: | The present study develops a new optimization algorithm to find the complete time-cost profile (Pareto front) over a set of feasible project durations, i.e., it solves the time-cost trade-off problem. To improve existing methods, the proposed algorithm aims to achieve three goals: (1) to obtain the entire Pareto front in a single run; (2) to be insensitive to the scales of time and cost; and (3) to treat all existing types of activity time-cost functions, such as linear, nonlinear, discrete, discontinuous, and a hybrid of the above. The proposed algorithm modifies a population-based search procedure, particle swarm optimization, by adopting an elite archiving scheme to store nondominated solutions and by aptly using members of the archive to direct further search. Through a fast food outlet example, the proposed algorithm is shown effective and efficient in conducting advanced bicriterion time-cost analysis. Future applications of the proposed algorithm are suggested in the conclusion. |
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Keywords: | Optimization Algorithms Computer aided scheduling Multiple objective analysis Construction industry |
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