An Integrated Multi-Criterion Decision-Making Analysis to Rank the Pareto-Front Solutions of Time-Cost Trade-Off Problems

Trade-off problems concentrate on balancing the main parameters of a project as completion time, total cost and quality of activities. In this study, the problem of project time-cost-quality trade-off is formulated and solved from a new standpoint. For this purpose, completion time and crash cost of project are illustrated as fuzzy goals, also the dependency of implementing time of each activity and its execution-quality is described by a fuzzy number. The overall quality of the project execution is defined as the minimum execution-quality of the project activities that should be maximized. Based on some real assumptions, a three-objective programming problem associated with the time-cost-quality trade-off problem is formulated; then with the aim of identifying a fair and appropriate trade-off, the research problem is reformulated as a single objective linear programming by utilizing a fuzzy decision-making methodology. Generating a final preferred solution, rather than a set of Pareto optimal solutions, and having a reasonable interpretation are two most important advantages of the proposed approach. To explain the practical performance of the proposed models and approach, a time-cost-quality trade-off problem for a project with real data is solved and analyzed.

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Fuzzy Multicriteria Decision-Making Model for Time-Cost-Risk Trade-Off Optimization in Construction Projects

Advances in Civil Engineering ◽

10.1155/2019/7852301 ◽

2019 ◽

Vol 2019 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

M. Ammar Alzarrad ◽

Gary P. Moynihan ◽

Muhammad T. Hatamleh ◽

Siyuan Song

Keyword(s):

Decision Making ◽

Construction Projects ◽

Multicriteria Decision Making ◽

Attractive Alternative ◽

Time Cost ◽

Analytic Hierarchy ◽

Trade Off ◽

Multicriteria Decision ◽

Trade Offs ◽

Cost Risk

As is often the case in project scheduling, when the project duration is shortened to decrease total cost, the total float is lost resulting in added critical or nearly critical activities. This, in turn, results in decreasing the probability of completing the project on time and increases the risk of schedule delays. To solve this problem, this research developed a fuzzy multicriteria decision-making (FMCDM) model. The objective of this model is to help project managers improve their decisions regarding time-cost-risk trade-offs (TCRTO) in construction projects. In this model, an optimization algorithm based on fuzzy logic and analytic hierarchy process (AHP) has been used to analyze the time-cost-risk trade-off alternatives and select the best one based on selected criteria. The algorithm was implemented in the MATLAB software and applied to two case studies to verify and validate the presented model. The presented FMCDM model could help produce a more reliable schedule and mitigate the risk of projects running overbudget or behind schedule. Further, this model is a powerful decision-making instrument to help managers reduce uncertainties and improve the accuracy of time-cost-risk trade-offs. The presented FMCDM model employed fuzzy linguistic terms, which provide decision-makers with the opportunity to give their judgments as intervals comparing to fixed value judgments. In conclusion, the presented FMCDM model has high robustness, and it is an attractive alternative to the traditional methods to solve the time-cost-risk trade-off problem in construction.

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Three Dimensional Time, Cost and Quality Tradeoff Optimization in Project Decision Making

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.5746 ◽

2012 ◽

Vol 433-440 ◽

pp. 5746-5752 ◽

Cited By ~ 3

Author(s):

Hadi Mokhtari ◽

Ali Salmasnia ◽

Mahdi Bastan

Keyword(s):

Decision Making ◽

Construction Projects ◽

Solution Method ◽

Computational Study ◽

Three Dimensional ◽

Time Cost ◽

Suggested Model ◽

Trade Off ◽

Robust Solution ◽

Overall Performance

Time, cost and quality are crucial aspects of each project and tradeoff among them is important for improvement of the overall performance of industrial and construction projects. In this paper we suggest that the quality is added into the traditional time-cost trade-off problem (TCTP) and develop a three dimensional time, cost and quality trade-off problem (TCQTP) with some realistic assumptions. To the best of our knowledge this problem has not been extensively treated in literature yet. In order to deal with the suggested stochastic TCQTP, a statistical robust solution method is adapted in which not only the correlations among objectives are considered but also the variance of objectives is minimized. A computational study on an illustrative example is done and the results support the applicability and reliability of the suggested model.

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Trading off Time–Cost–Quality in Construction Project Scheduling Problems with Fuzzy SWARA–TOPSIS Approach

Buildings ◽

10.3390/buildings11090387 ◽

2021 ◽

Vol 11 (9) ◽

pp. 387

Author(s):

Sayyid Ali Banihashemi ◽

Mohammad Khalilzadeh ◽

Jurgita Antucheviciene ◽

Jonas Šaparauskas

Keyword(s):

Decision Making ◽

Project Scheduling ◽

Construction Projects ◽

Construction Project ◽

Solution Technique ◽

Time Cost ◽

Trade Off ◽

Project Activity ◽

Project Objectives ◽

Construction Project Scheduling

The increasing number of construction projects together with the limited resources of organizations led to tough competition for achieving project goals. Time, cost, and quality have been known as the project iron triangle. Project managers attempt to allocate the appropriate resources and make the best decisions for accomplishing projects with the shortest durations, lowest costs, and the highest quality. No study has examined the time–cost–quality trade-off problem with decision-making approaches. In this study, the fuzzy multi-criteria decision-making (MCDM) methods are exploited to choose the best mode for performing each activity. For this purpose, the SWARA method is applied to determine the importance weights of time, cost, and quality. In addition, the TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) technique is used to rank and select the best activity execution modes. The proposed model is implemented on two medium- and large-size construction projects to evaluate its efficiency. Several execution modes with fuzzy duration, cost, and quality are considered for each project activity. Finally, sensitivity analysis is conducted taking three different conditions into account: the shortest duration of the execution modes, the lowest cost of the execution modes, and the highest quality of execution modes for each activity. The solution of each trade-off is compared with the solution obtained from the fuzzy SWARA–TOPSIS method. The schedule is developed according to the best execution mode for each project activity. The obtained results in two different construction projects show significant improvements in the overall project objectives so that the projects can be completed in fewer durations and costs along with higher quality. Because of the higher importance of cost, the cost of each activity is closer to the lowest cost. The activity duration is also closer to the most likely duration, and quality is closer to the high-quality level. The application of this approach can create new opportunities for research and knowledge development in the field of construction project scheduling.

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The Effect of Different Decision-Making Methods on Multi-Objective Optimisation of Predictive Torque Control Strategy

Power Electronics and Drives ◽

10.2478/pead-2021-0018 ◽

2021 ◽

Vol 6 (1) ◽

pp. 289-300

Author(s):

Aycan Gurel ◽

Emrah Zerdali

Keyword(s):

Decision Making ◽

Pareto Front ◽

Electric Machines ◽

Operating Conditions ◽

Torque Control ◽

Nsga Ii ◽

Clear Trend ◽

Electric Cars ◽

Weighting Factors ◽

Front Solutions

Abstract Today, a clear trend in electrification process has emerged in all areas to cope with carbon emissions. For this purpose, the widespread use of electric cars and wind energy conversion systems has increased the attention and importance of electric machines. To overcome limitations in mature control techniques, model predictive control (MPC) strategies have been proposed. Of these strategies, predictive torque control (PTC) has been well accepted in the control of electric machines. However, it suffers from the selection of weighting factors in the cost function. In this paper, the weighting factor associated with the flux error term is optimised by the non-dominated sorting genetic algorithm (NSGA-II) algorithm through torque and flux errors. The NSGA-II algorithm generates a set of optimal solutions called Pareto front solutions, and a possible solution must be selected from among the Pareto front solutions for use in the PTC strategy. Unlike the current literature, three decision-making methods are applied to the Pareto front solutions and the weighting factors selected by each method are tested under different operating conditions in terms of torque ripples, flux ripples, cur-rent harmonics and average switching frequencies. Finally, a decision-making method is recommended.

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Time-Cost-Quality Trade-off Model for Optimal Pile Type Selection Using Discrete Particle Swarm Optimization Algorithm

Civil Engineering Journal ◽

10.28991/cej-2019-03091424 ◽

2019 ◽

Vol 5 (11) ◽

pp. 2461-2471

Author(s):

Hanaa H. Lateef ◽

Abbas Mohammed Burhan

Keyword(s):

Decision Making ◽

Particle Swarm Optimization ◽

Pso Algorithm ◽

Pile Foundations ◽

Time Cost ◽

Multi Objective Optimization ◽

Swarm Optimization ◽

Trade Off ◽

Multi Objective ◽

Pile Type

The cost of pile foundations is part of the super structure cost, and it became necessary to reduce this cost by studying the pile types then decision-making in the selection of the optimal pile type in terms of cost and time of production and quality .So The main objective of this study is to solve the time–cost–quality trade-off (TCQT) problem by finding an optimal pile type with the target of "minimizing" cost and time while "maximizing" quality. There are many types In the world of piles but in this paper, the researcher proposed five pile types, one of them is not a traditional, and developed a model for the problem and then employed particle swarm optimization (PSO) algorithm, as one of evolutionary algorithms with the help of (Mat lab software), as a tool for decision making problem about choosing the best alternative of the traded piles, and proposes a multi objective optimization model, which aims to optimize the time, cost and quality of the pile types, and assist in selecting the most appropriate pile types. The researcher selected 10 of senior engineers to conduct interviews with them. And prepared some questions for interviews and open questionnaire. The individuals are selected from private and state sectors each one have 10 years or more experience in pile foundations work. From personal interviews and field survey the research has shown that most of the experts, engineers are not fully aware of new soft wear techniques to helps them in choosing alternatives, despite their belief in the usefulness of using modern technology and software. The Problem is multi objective optimization problem, so after running the PSO algorithm it is usual to have more than one optimal solution, for five proposed pile types, finally the researcher evaluated and discussed the output results and found out that pre-high tension spun (PHC)pile type was the optimal pile type.

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Pareto Explorer for Finding the Knee for Many Objective Optimization Problems

Mathematics ◽

10.3390/math8101651 ◽

2020 ◽

Vol 8 (10) ◽

pp. 1651

Author(s):

Oliver Cuate ◽

Oliver Schütze

Keyword(s):

Decision Making ◽

Pareto Front ◽

Recent Trend ◽

Optimization Problems ◽

Finite Size ◽

Entire Solution ◽

Decision Making Process ◽

Trade Off ◽

Decision Making Processes ◽

Exploration Tool

Optimization problems where several objectives have to be considered concurrently arise in many applications. Since decision-making processes are getting more and more complex, there is a recent trend to consider more and more objectives in such problems, known as many objective optimization problems (MaOPs). For such problems, it is not possible any more to compute finite size approximations that suitably represent the entire solution set. If no users preferences are at hand, so-called knee points are promising candidates since they represent at least locally the best trade-off solutions among the considered objective values. In this paper, we extend the global/local exploration tool Pareto Explorer (PE) for the detection of such solutions. More precisely, starting from an initial solution, the goal of the modified PE is to compute a path of evenly spread solutions from this point along the Pareto front leading to a knee of the MaOP. The knee solution, as well as all other points from this path, are of potential interest for the underlying decision-making process. The benefit of the approach is demonstrated in several examples.

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A novel multi criteria decision making model for optimizing time–cost–quality trade-off problems in construction projects

Expert Systems with Applications ◽

10.1016/j.eswa.2014.11.032 ◽

2015 ◽

Vol 42 (6) ◽

pp. 3089-3104 ◽

Cited By ~ 90

Author(s):

Shahryar Monghasemi ◽

Mohammad Reza Nikoo ◽

Mohammad Ali Khaksar Fasaee ◽

Jan Adamowski

Keyword(s):

Decision Making ◽

Construction Projects ◽

Multi Criteria Decision Making ◽

Time Cost ◽

Trade Off ◽

Decision Making Model

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A Framework for Time-Cost-Quality Optimization in Project Management Problems Using an Exploratory Grid Concept in the Multi-Objective Simulated-Annealing

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622021500322 ◽

2021 ◽

pp. 1-26

Author(s):

Alzira Mota ◽

Paulo Ávila ◽

Ricardo Albuquerque ◽

Lino Costa ◽

João Bastos

Keyword(s):

Decision Making ◽

Simulated Annealing ◽

Optimization Problems ◽

Decision Makers ◽

Time Cost ◽

Trade Off ◽

Multi Objective ◽

Pareto Optimal Set ◽

Criteria Weights ◽

Optimal Set

Time, cost, and quality are the three indispensable factors for the realization and success of a project. In this context, we propose a framework composed of a multi-objective approach and multi-criteria decision-making methods (MCDM) to solve time-cost-quality trade-off optimization problems. A multi-objective Simulated Annealing (MOSA) algorithm is used to compute an approximation to the Pareto optimal set. The concept of the exploratory grid is introduced in the MOSA to improve its performance. MCDM are used to assist the decision-making process. The Shannon entropy and AHP methods assign weights to criteria. The first methodology is for the inexperienced decision-makers, and the second concedes a personal and flexible weighting of the criteria weights, based on the project manager’s assessment. The TOPSIS and VIKOR methods are considered to rank the solutions. Although they have the same purpose, the rankings achieved are different. A tool is implemented to solve a time-cost-quality trade-off problem on a project activities network. The computational experiments are analyzed and the results with the exploratory grid in Simulated Annealing (SA) are promising. Despite the framework aims to solve multi-objective trade-off optimization problems, supporting the decisions of the project manager, the methodologies used can also be applied in other areas.

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