Time-cost-quality-environmental impact trade-off resource-constrained project scheduling problem with DEA approach

Banihashemi, Sayyid Ali; Khalilzadeh, Mohammad

doi:10.1108/ecam-05-2020-0350

Cited by 31 publications

(16 citation statements)

References 39 publications

(29 reference statements)

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“…Keshavarz and Shoul (2020) used a single-objective optimization approach to solve the TCQ trade-off problem [21]. considered the multi-mode project scheduling problem and evaluated the efficiency of each mode in terms of time, cost, quality, and environmental impacts [22]. Mao et al (2020) Presented a mathematical model in shipbuilding project scheduling problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Three Metaheuristic Algorithms to Time-Cost-Quality Trade-Off Project Scheduling Problem for Construction Projects Considering Time Value of Money

et al. 2021

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Time, cost, and quality have been known as the project iron triangles and substantial factors in construction projects. Several studies have been conducted on time-cost-quality trade-off problems so far, however, none of them has considered the time value of money. In this paper, a multi-objective mathematical programming model is developed for time-cost-quality trade-off scheduling problems in construction projects considering the time value of money, since the time value of money, which is decreased during a long period of time, is a very important matter. Three objective functions of time, cost, and quality are taken into consideration. The cost objective function includes holding cost and negative cash flows. In this model, the net present value (NPV) of negative cash flow is calculated considering the costs of non-renewable (consumable) and renewable resources in each time period of executing activities, which can be mentioned as the other contribution of this study. Then, three metaheuristic algorithms including multi-objective grey wolf optimizer (MOGWO), non-dominated sorting genetic algorithm (NSGA-II), and multi-objective particle swarm optimization (MOPSO) are applied, and their performance is evaluated using six metrics introduced in the literature. Finally, a bridge construction project is considered as a real case study. The findings show that considering the time value of money can prevent cost overrun in projects. Additionally, the results indicate that the MOGWO algorithm outperforms the NSGA-II and MOPSO algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

Application of Three Metaheuristic Algorithms to Time-Cost-Quality Trade-Off Project Scheduling Problem for Construction Projects Considering Time Value of Money

et al. 2021

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“…In addition, it is one of the widely used methods to evaluate and rank combat tasks by using various evaluation methods. For example, an evaluation method combining the Analytical Hierarchy Process (AHP) method and fuzzy mathematics [33][34][35], Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method in dynamic environment [36][37][38], Data Envelopment Analysis (DEA) method which is less affected by the subjective factors of decision makers [39][40][41], and entropy method combined with the above method [42,43], etc.…”

Section: Moeas For Operational Task Schedulingmentioning

confidence: 99%

A multi-objective scheduling method for operational coordination time using improved triangular fuzzy number representation

2021

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In modern warfare, the comprehensiveness of combat domain and the complexity of tasks pose great challenges to operational coordination.To address this challenge, we use the improved triangular fuzzy number to express the combat mission time, first present a new multi-objective operational cooperative time scheduling model that takes the fluctuation of combat coordinative time and the time flexibility between each task into account. The resulting model is essentially a large-scale multi-objective combinatorial optimization problem, intractably complicated to solve optimally. We next propose multi-objective improved Bat algorithm based on angle decomposition (MOIBA/AD) to quickly identify high-quality solutions to the model. Our proposed algorithm improves the decomposition strategy by replacing the planar space with the angle space, which helps greatly reduce the difficulty of processing evolutionary individuals and hence the time complexity of the multi-objective evolutionary algorithm based on decomposition (MOEA/D). Moreover, the population replacement strategy is enhanced utilizing the improved bat algorithm, which helps evolutionary individuals avoid getting trapped in local optima. Computational experiments on multi-objective operational cooperative time scheduling (MOOCTS) problems of different scales demonstrate the superiority of our proposed method over four state-of-the-art multi-objective evolutionary algorithms (MOEAs), including multi-objective bat Algorithm (MOBA), MOEA/D, non-dominated sorting genetic algorithm version II (NSGA-II) and multi-objective particle swarm optimization algorithm (MOPSO). Our proposed method performs better in terms of four performance criteria, producing solutions of higher quality while keeping a better distribution of the Pareto solution set.

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“…On the other hand, the main reason for project delays is a lack of proper resource-constrained scheduling [12]. In a resource-constrained environment, typical time-cost trade-off analyses are discussed, and moreover, the overall evaluations of project performance in regard to quality and environmental impacts should be further considered [51,52]. The RCPSP framework was adopted to solve scheduling problems in project management, manufacturing planning, and construction management.…”

Section: Literature Reviewmentioning

confidence: 99%

Two-Stage Optimization Model for Life Cycle Maintenance Scheduling of Bridge Infrastructure

2020

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As bridge infrastructure ages, the deterioration of materials and hazard events reduce the service quality and compromise the safety of the structure. Therefore, there is a tremendous need for bridge maintenance planning, and such maintenance studies during recent years have focused on the life cycle aspect. To fulfill the budget requirements of life cycle maintenance, an important issue is to ensure that the limited maintenance budget is utilized in an effective way. However, there are few studies that have aimed to assess the topic of budget allocation and the adjustment of bridge life-cycle maintenance issues. In order to resolve such issues, a two-stage optimization model based on constraint programming (CP) is proposed in this study to deal with maintenance scheduling problems. This is facilitated by adopting the resource-constrained project scheduling problem (RCPSP) framework, in which, three plans according to the maintenance time point are considered (i.e., early, middle, and late plans). According to the RCPSP concepts, this study views the budget ceiling as the resource limit, and maintenance plans as activities, so that the feasibility of each maintenance plan depends on the sufficiency of the budget. As the first stage, Model-I (the life cycle lifespan evaluation model) takes a life cycle perspective, evaluating how long it will take to keep all bridges in a serviceable condition with minimum expenditure over the planning cycle, and evaluates the annual budgets that can be used as a reference for users to draft a budget plan. Based on the planning result from Model-I and the actual annual budget approved for the current year, the second stage, Model-II (the annual budget allocation model) then reallocates the actual budget to take into account the importance of all bridges and different costs and benefits of maintenance plans, and revises the suggested annual budget values obtained by Model-I for the following years. Through a case study, the optimized result demonstrates that annual recursive implementation of this two-stage model satisfies the need to adjust existing budgetary data, and provides management personnel with optimized and realistic maintenance decision support for bridge infrastructure.

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Time-cost-quality-environmental impact trade-off resource-constrained project scheduling problem with DEA approach

Cited by 31 publications

References 39 publications

Application of Three Metaheuristic Algorithms to Time-Cost-Quality Trade-Off Project Scheduling Problem for Construction Projects Considering Time Value of Money

Application of Three Metaheuristic Algorithms to Time-Cost-Quality Trade-Off Project Scheduling Problem for Construction Projects Considering Time Value of Money

A multi-objective scheduling method for operational coordination time using improved triangular fuzzy number representation

Two-Stage Optimization Model for Life Cycle Maintenance Scheduling of Bridge Infrastructure

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