A novel multi criteria decision making model for optimizing time–cost–quality trade-off problems in construction projects. Issue 6 (15th April 2015) - Monghasemi, Shahryar; Nikoo, Mohammad Reza; Khaksar Fasaee, Mohammad Ali; Adamowski, Jan
Highlights: Using evidential reasoning as the multi-criterion decision making (MCDM) approach. A comprehensive framework to integrate MCDM methods with optimization techniques. Using MOGA with NSGA-II to solve discrete time–cost–quality trade-off problem. Determining the weights of the objectives with Shannon's Entropy technique. Obtaining all the Pareto solutions for the 18-activity network benchmark example. Abstract: The planning phase of every construction project is entangled with multiple and occasionally conflicting criteria which need to be optimized simultaneously. Multi-criterion decision-making (MCDM) approaches can aid decision-makers in selecting the most appropriate solution among numerous potential Pareto optimal solutions. An evidential reasoning (ER) approach was applied for the first time in the context of project scheduling to identify the best Pareto solution for discrete time–cost–quality trade-off problems (DTCQTPs). An exhaustive framework to synthesize the MCDM approaches with multi-objective optimization techniques was also proposed. To identify all global Pareto optimal solutions, a multi-objective genetic algorithm (MOGA) incorporating the NSGA-II procedure was developed and tested in a highway construction project case study. The Shannon's entropy technique served to determine the relative weights of the objectives according to their contributions to the uncertainty of the results obtained. A benchmark case study of DTCQTP was solved using the proposed methodology, and the Pareto optimal solutions obtained were subsequently ranked using the ER approach. By investigating the performance of each scheduling alternative based on multiple criteria (e.g., time, cost, and quality), the proposed approach proved effective in raising the efficiently of construction project scheduling.