Modeling and Solving Project Portfolio and Contractor Selection Problem Based on Project Scheduling under Uncertainty

Namazian, Ali; Yakhchali, Siamak Haji

doi:10.1016/j.sbspro.2016.06.159

Cited by 11 publications

(4 citation statements)

References 20 publications

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“…However, this has been found to be highly inadequate, both in terms of incorporation and assessment of multiple-criteria like environmental and wider economic issues which are usually essentially difficult to quantify, and because traditional CBA relies heavily on estimating both demand forecasts and construction costs [1][2][3]. Over the years, various researchers dealt with such aspects of project performance, claiming that demand forecasts and construction cost estimations in particular are subject to a large degree of uncertainty-commonly referred to as optimism bias [4][5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor

2021

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A way to minimize uncertainty and achieve the best possible project performance in construction project management can be achieved during the procurement process, which involves selecting an optimal contractor according to “the most economically advantageous tender.” As resources are limited, decision-makers are often pulled apart by conflicting demands coming from various stakeholders. The challenge of addressing them at the same time can be modelled as a multi-criteria decision-making problem. The aim of this paper is to show that the analytic hierarchy process (AHP) together with PROMETHEE could cope with such a problem. As a result of their synergy, a decision support concept for selecting the optimal contractor (DSC-CONT) is proposed that: (a) allows the incorporation of opposing stakeholders’ demands; (b) increases the transparency of decision-making and the consistency of the decision-making process; (c) enhances the legitimacy of the final outcome; and (d) is a scientific approach with great potential for application to similar decision-making problems where sustainable decisions are needed.

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Section: Introductionmentioning

confidence: 99%

A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor

2021

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“…Chakrabortty et al (2016) proposed a reactive rescheduling procedure without having any disruption information in advance. Namazian and Yakhchali (2016) investigated a project portfolio selection problem based on the schedule of the project in the uncertain nature of durations of the activities. Mehmanchi and Shadrokh (2013) with considering the effect of learning and forgetting on the human skills developed an exponential learning function by assuming the efficiency of employees performing.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Modeling and solving multi-skilled resource-constrained project scheduling problem with calendars in fuzzy condition

Ahmadpour

Ghezavati

2019

J Ind Eng Int

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In this study, we aim to present a new model for the resource-constrained project scheduling problem (RCPSP) considering a working calendar for project members and determined the skill factor of any member using the efficiency concept. For this purpose, the recyclable resources are staff resources where any person with multiple skills can meet the required skills of activities in a given time. Then, considering uncertainty condition for parameters, it provided a fuzzy scheduling model and validated models by solving different examples. The proposed mathematical programming model optimizes the allocation of limited resources to project activities for scheduling purposes in an essential activity in the real condition of scheduling problems. Moreover, the proposed model can decrease the risk of deviation from scheduling by allocating members with higher skill factors to critical activities. Then, considering uncertainty condition for parameters, it provided a fuzzy scheduling model and validated models by solving different examples. Considering fuzzy conditions for the calendar of the project and multi-skill operators are firstly considered in this paper. Also, the recyclable resources are staff resources which are being considered for the model concurrently in response to the risks of availability to resources and delay in completing the project under uncertainty. The results derived from the model solved by CPLEX indicated a decreased need for employment and shortened project completion duration. Assuming the uncertainty of available resource capacity at any time, the results obtained from the fuzzy model for the value of objective function were evaluated under the influence of the resource calendar and showed the benefits. Effect of the multi-skill members with calendar constraints on the model is tested, and the advantages are determined.

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“…Some studies have used these methods for the project selection problem. Namazian and Haji Yakhchali [4] developed a project portfolio selection problem based on the schedule of the projects so that the minimum expected pro t would be met in the shortest possible time period. In their research, because of their uncertain nature, durations of the activities were considered as semi-trapezoidal fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

Integrated bi-objective project selection and scheduling using Bayesian Networks: A risk- based approach

2019

Self Cite

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This paper presents a novel formulation for the integrated bi-objective problem of project selection and scheduling. The rst objective was to minimize the aggregated risk by evaluating the expected value of schedule delay and the second objective was to maximize the achieved bene t. To evaluate the expected aggregated impacts of risks, an objective function based on the Bayesian Networks was proposed. In the extant mathematical models of the joint problem of project selection and scheduling, projects are selected and scheduled without considering the risk network of the projects indicating the individual and interaction e ects of risks impressing the duration of the activities. To solve the model, two solution approaches were developed, one exact and one metaheuristic approach. Goal Programming (GP) method was adopted to optimally select and schedule projects. Since the problem was NP-hard (Non-deterministic Polynomial-time), an algorithm combining GP method and Genetic Algorithm (GA) was proposed, hence named GPGA. Finally, the e ciency of the proposed algorithm was assessed not only based on small-size instances, but also by generating and testing representative datasets of larger instances. The results of the computational experiments indicated that it had acceptable performance in handling large-size and more realistic problems.

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Modeling and Solving Project Portfolio and Contractor Selection Problem Based on Project Scheduling under Uncertainty

Cited by 11 publications

References 20 publications

A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor

A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor

Modeling and solving multi-skilled resource-constrained project scheduling problem with calendars in fuzzy condition

Integrated bi-objective project selection and scheduling using Bayesian Networks: A risk- based approach

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