Abstract
In the construction management planning, both the client and the contractor are interested in completing the project within the planned schedule. To achieve it, time-cost trade-off problem (TCTP) is carried-out to obtain the optimal set of time-cost alternatives. Although Pareto front solutions are not preferred to each other, the decision-maker (DM) has to choose only the best solution. The DMs are neither well-educated nor have adequate knowledge to make proper decisions. Thus, such a choice has to be made through additional preferences not included in the original formulation of the optimization problem. To better support the meta-heuristic optimization outputs, in this paper, an integration of entropy weight, simple additive weighting (SAW), and technique for order of preference by similarity to ideal solution (TOPSIS) are modelled to solve the MCDM problem, while the Teaching Learning Based Optimization (TLBO) algorithm is applied to solve the proposed multi-objective decision-making model. In the proposed model, the weights selections are done objectively to demonstrate the variation on the rankings of MCDM approaches. While the entropy technique served to determine the weight of the criteria from the original matrix data objectively and the TOPSIS method is employed to rank the alternative Pareto front solutions. The proposed methodology is utilized to rank a set of Pareto optimal solutions of well-known optimization problems. The obtained results are compared against the rankings provided by (SAW) approach to investigate the efficiency of the proposed model. Results demonstrate that the present model can be a favorable decision-making model for the decision-makers.
Highlights
In construction management field, optimization is a very useful tool to meet the desired objectives under the given constraints
The planners have to execute analysis to compromise between time and cost of a project which is known as time cost trade-off problem (TCTP) in the literature
The main objectives of this study is to propose an integrated approach, which uses the MCDM techniques into the body of Teaching Learning Based Optimization (TLBO) algorithm for the selection of Pareto-optimal solutions in TCTP problems, and to compare the findings of TOPSIS with simple additive weighting (SAW) techniques
Summary
Optimization is a very useful tool to meet the desired objectives under the given constraints. In this field, somewhere in the region of every real-world problem includes simultaneous optimization of often competing objectives. Somewhere in the region of every real-world problem includes simultaneous optimization of often competing objectives Both the client as well as the contractor tend to have the objectives e.g. time, cost or other targets efficiently be accomplished on schedule. One of the fundamental and most straightforward multi-criteria decision making procedures is sum of the weight calculation model. In this method, a weight is appointed to every rule to exhibit its significance
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