A hybrid simulation-optimization approach for the robust Discrete Time/Cost Trade-off Problem

Said, Samer Said Abdulla; Haouari, Mohamed

doi:10.1016/j.amc.2015.02.092

Cited by 24 publications

(10 citation statements)

References 32 publications

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“…An adaptive-hybrid genetic algorithm was proposed by Zheng 27 for time–cost–quality trade-off problems. Said and Haouari 28 developed a model wherein the simulation–optimization strategy and the mixed-integer programming formulation were used to solve the DTCTP. Tran, Luong-Duc 29 presented an opposition multiple objective symbiotic organisms search (OMOSOS) model for time, cost, quality, and work continuity trade-off in repetitive projects.…”

Section: Literature Reviewmentioning

confidence: 99%

Solving large-scale discrete time–cost trade-off problem using hybrid multi-verse optimizer model

Son

Dang

2023

Sci Rep

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The analysis of the relationship between time and cost is a crucial aspect of construction project management. Various optimization techniques have been developed to solve time–cost trade-off problems. A hybrid multi-verse optimizer model (hDMVO) is introduced in this study, which combines the multi-verse optimizer (MVO) and the sine cosine algorithm (SCA) to address the discrete time–cost trade-off problem (DTCTP). The algorithm's optimality is evaluated by using 23 well-known benchmark test functions. The results demonstrate that hDMVO is competitive with MVO, SCA, the dragonfly algorithm and ant lion optimization. The performance of hDMVO is evaluated using four benchmark test problems of DTCTP, including two medium-scale instances (63 activities) and two large-scale instances (630 activities). The results indicate that hDMVO can provide superior solutions in the time–cost optimization of large-scale and complex projects compared to previous algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

Solving large-scale discrete time–cost trade-off problem using hybrid multi-verse optimizer model

Son

Dang

2023

Sci Rep

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“…Basically, S scenarios of the duration and quality of the different modes of each task should be randomly generated. Similarly to previous works [19]- [21]. We assume that P jm the random variable that measures the duration of each task j in the execution mode m is lognormal distributed and we assume that its mean duration µ jm is equal to its nominal duration and its standard deviation σ jm is equal to 0.25 µ * jm ( P jm Lognormal(µ jm , σ jm )).…”

Section: Monte-carlo Simulationmentioning

confidence: 99%

Risk Assessment for Discrete Stochastic Time-Cost-Quality Trade-Off Problem Using Simulation-Based Integer Linear Programming Approach

Mrad

Al-Gahtani

Hulchafo³

et al. 2019

IEEE Access

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Time, quality, and cost are the most critical performance indicators in project management. It has always been considered a tough challenge for project managers to optimize them simultaneously. This paper aims at establishing a simulation-based integer linear programming tool that helps project managers, at the preliminary stages, to assess the risks related to the feasibility and profitability of the projects within the framework of a stochastic discrete time-cost-quality tradeoff problem. The computational experiments on a wide range of benchmark instances from the literature were performed, and the results were compared with those of the deterministic version of the problem. The proposed approach is able to assess the impact of the stochastic behavior of the duration and the quality of the tasks on the cost, duration, and quality of the whole project. Moreover, the simplicity and the reduced time required for the computation of large size networks revealed to be very promising for giving a practical solution for real-life projects. INDEX TERMS Monte-Carlo simulation, integer linear programming, project management, risk.

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“…At the same time, CTP can be solved by fast polynomial algorithms (see, e.g., [10,19]), while the discrete version of trade-off problems, with the exception of a few kinds of project networks [5] is an NP-hard problem [6]; therefore, the discrete version of timequality-cost trade-off problems are also NP-hard problems [25]. To solve DTPs, heuristic and metaheuristic algorithms are usually applied [23,26]. The recent multimode resourceconstrained project scheduling problems (MRCPSP) (see an excellent review in Habibi et al [11]), do not assume any trade-off functions between time and resources or between time and cost (see Fig.…”

Section: Introductionmentioning

confidence: 99%

Multimode resource-constrained project scheduling in flexible projects

Kosztyán

Szalkai

2019

J Glob Optim

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Flexible agile and extreme project management methods have become increasingly popular among practitioners, particularly in the IT and R&D sectors. In contrast to the theoretically and algorithmically well-established and developed trade-off and multimode methods applied in traditional project management methods, flexible project scheduling methods, which are applied in agile, hybrid, and especially extreme project management, lack a principled foundation and algorithmic handling. The aim of this paper is to fill this gap. We propose a matrix-based method that provides scores for alternative project plans that host flexible task dependencies and undecided, supplementary task completion while also handling the new but unplanned tasks. In addition, traditional multimode resource-constrained project scheduling problems are also covered. The proposed method can bridge the flexible and traditional approaches.

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A hybrid simulation-optimization approach for the robust Discrete Time/Cost Trade-off Problem

Cited by 24 publications

References 32 publications

Solving large-scale discrete time–cost trade-off problem using hybrid multi-verse optimizer model

Solving large-scale discrete time–cost trade-off problem using hybrid multi-verse optimizer model

Risk Assessment for Discrete Stochastic Time-Cost-Quality Trade-Off Problem Using Simulation-Based Integer Linear Programming Approach

Multimode resource-constrained project scheduling in flexible projects

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