A multi-objective stochastic programming model for project-oriented human-resource management optimization

Rahmanniyay, Fahimeh; Yu, Andrew Junfang

doi:10.1080/17509653.2018.1534220

Cited by 22 publications

(12 citation statements)

References 40 publications

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“…In comparison to the other three actors who play a single role in the financial activities, the contractor is both the payer and the payee; hence, may confront more with conflict than the other players. The payment conflicts were found to be common in other researches; Rahmanniyay & Yu, 2019;Vahdani & Shams, 2019).…”

Section: The Allocation Of Conflict In Program Teammentioning

confidence: 86%

A Systematic Approach to Effective Conflict Management for Program

Wang

2020

SAGE Open

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Due to the complex structure and stakeholder relationships within a program, the management of conflicts in program therein proves more challenging than with a single project. The internal conflict of a program affects the performance of the program team and the success of the program. The previous researches focus more on the project level rather than program level, and lack a systematic analysis of management mechanism of team conflict. This research contributes to the program conflict literature by investigating the unique nature and solutions of conflict within program team, taking a systematic and innovative view on the organizational structure of a complex construction program. The findings reveal unique program conflict and their causes and impacts, and suggest the principles and alternative resolution strategies for conflict in program. The different roles of stakeholders in program conflict are analyzed by social network method. A program conflict management model is developed for the effective management of program conflicts. The model provides a systematic view of the learning cycle of program conflict management, including conflict identification, resolution, feedback, and prevention, of which many patterns are found distinct from project conflict management. The research results can benefit practitioners and researchers in better understanding and minimizing program conflict.

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Section: The Allocation Of Conflict In Program Teammentioning

confidence: 86%

A Systematic Approach to Effective Conflict Management for Program

Wang

2020

SAGE Open

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“…When uncertain factors are involved, many scholars regard them as random phenomena and put forward stochastic multi-objective programming (SMP). SMP is generally closer to practical problems and has been widely developed in many areas of application, which can be referred to in References [6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Research on Comparision between Deterministic Method and Uncertain Method for Solving Uncertain Multiobjective Programming

et al. 2022

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Since there are often few or no samples and asymmetry information in the problems, uncertainty theory is introduced to study uncertain multi-objective programming (UMP), which cannot be solved by probability theory. Generally speaking, there are two types of methods for solving the UMP problem: in deterministic method, using the numerical characteristics of an uncertain variable, the UMP problem is transformed into a deterministic multiobjective programming, and then solved by the weighting method and ideal point method; in the uncertain method, the UMP problem is transformed into an uncertain single-objective programming, and then is solved by the evaluation criteria of the uncertain variables. The theoretical analysis and the data results for numerical examples solved by the AC algorithm designed in the paper show that the two types of methods are obviously different. Further, using this comparison, the essential difference between the two methods is whether the uncertainty relation between objective functions sholud be considered. Therefore, when the uncertainty relation is closely related, the uncertain method is more appropriate; otherwise, the deterministic method should be chosen.

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“…Farrokh et al [38] studied the closed loop supply chain network design under hybrid uncertainty with the use of fuzzy stochastic programming. Rahmanniyay and Yu [39] introduced a new multi-objective mathematical model in which objective functions optimize cost and competency simultaneously to develop a project team for multidisciplinary projects under uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Multi-Objective Programming Problem: A Two-Phase Weighted Coefficient Approach

Khalifa¹,

Kumar²,

Alodhaibi³

2021

MMEP

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This paper deals with multi-objective stochastic linear programming problem. The problem is considered by introducing the coefficients of the decision variables and the right-hand-side parameters in the constraints as normal random variables. A method for converting the problem into its deterministic problem is proposed and hence two- phase approach with equal weights is proposed for finding an efficient solution. The advantages of the approach are: as weights which is positive, not necessarily equal and generate an efficient solution. A numerical example is given to illustrate the suggested methodology.

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A multi-objective stochastic programming model for project-oriented human-resource management optimization

Cited by 22 publications

References 40 publications

A Systematic Approach to Effective Conflict Management for Program

A Systematic Approach to Effective Conflict Management for Program

Research on Comparision between Deterministic Method and Uncertain Method for Solving Uncertain Multiobjective Programming

Stochastic Multi-Objective Programming Problem: A Two-Phase Weighted Coefficient Approach

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