Multiple Resources Leveling in Multiple Projects Scheduling Problem Using Particle Swarm Optimization

Yan, Guo; Li, Nan; Ye, Tingting

doi:10.1109/icnc.2009.142

Cited by 7 publications

(9 citation statements)

References 2 publications

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“…The optimization model aims at minimizing the fluctuation in using resources by reducing the peak demand resources and daily resource consumption. The definition of resource leveling in multiple projects can be expressed as an optimization problem as follows [14,55]:…”

Section: Description Of Resource Leveling In Multiple Projectsmentioning

confidence: 99%

Robust forensic-based investigation algorithm for resource leveling in multiple projects

Tran¹,

Le²,

Nguyen³

et al. 2022

Scientia Iranica

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The project managers often face challenging due to a scarcity of resources in construction management. Levelling the used resources in multiple projects is a frequently encountered problem in construction areas and manufacturing sectors. This study proposes a robust forensic-based investigation (FBI) algorithm for resource leveling in multiple projects with considerations of different objective functions of resource graphs. The fuzzy c-means clustering approach is fused into the main operation of the FBI to enhance the rate of convergence by utilizing population information. The scheduling examines different objective functions for optimizing resource profile selection. Two application case studies are used to demonstrate the performance of the improved optimization algorithm in dealing with the resource-leveling problem in multiple projects. Experimental findings and statistical comparisons demonstrated that the developed FFBI could acquire high quality solutions and surpass those of compared optimization algorithms.

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Section: Description Of Resource Leveling In Multiple Projectsmentioning

confidence: 99%

Robust forensic-based investigation algorithm for resource leveling in multiple projects

Tran¹,

Le²,

Nguyen³

et al. 2022

Scientia Iranica

View full text Add to dashboard Cite

show abstract

“…Multiple-resources leveling in multiple-projects scheduling differs from conventional resource leveling primarily as described in the following paragraphs (Guo et al 2009). First, because of differing levels of resource demand, assimilation must transform absolute demand into relative demand to enable all p resources to be comparable in terms of quantity.…”

Section: Multiple-resources Leveling In the Multiple-projects Problemmentioning

confidence: 99%

“…A case study adapted from Guo et al (2009) was used to demonstrate the capability of the newly developed DSOS-MRLMP model. In this case study, an enterprise had to start two projects with the same total project duration.…”

Section: Case Studymentioning

confidence: 99%

“…However, multiple-resources leveling in multiple-projects scheduling (MRLMP) is the most typical scenario in the construction and manufacturing industries. It is relatively more complex and difficult to solve and lacks a standard handling procedure (Guo et al 2009). Thus, developing a more efficient optimization algorithm for MRLMP problems and achieving better resource-leveling solutions are essential to improving the management of construction project resources.…”

Section: Introductionmentioning

confidence: 99%

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Optimizing Multiple-Resources Leveling in Multiple Projects Using Discrete Symbiotic Organisms Search

Cheng

Prayogo

Tran

2016

J. Comput. Civ. Eng.

100

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Resource leveling is used in project scheduling to reduce fluctuation in resource usage over the period of project implementation. Fluctuating resource usage frequently creates the untenable requirement of regularly hiring and firing temporary staff to meet short-term project needs. Construction project decision makers currently rely on experience-based methods to manage fluctuations. However, these methods lack consistency and may result in unnecessary waste of resources or costly schedule overruns. This research introduces a novel discrete symbiotic organisms search for optimizing multiple resources leveling in the multiple projects scheduling problem (DSOS-MRLMP). The optimization model proposed is based on a recently developed metaheuristic algorithm called symbiotic organisms search (SOS). SOS mimics the symbiotic relationship strategies that organisms use to survive in the ecosystem. Experimental results and statistical tests indicate that the proposed model obtains optimal results more reliably and efficiently than do the other optimization algorithms considered. The proposed optimization model is a promising alternative approach to assisting project managers in handling MRLMP effectively.

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“…In recent years, advanced computational methods like Genetic Algorithms (GAs) [6,9,[19][20][21][22][23][24][25][26] and particle swarm optimization approaches [27,28] have been used for solving resource leveling problems. Also, Kartam and Tongthong [29] introduced a methodology for solving resource leveling problems using Artificial Neural Networks (ANN).…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Evolutionary Algorithms in Project Management

Kyriklidis

Dounias

2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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The paper deals with "resource leveling optimization problems", a class of problems that are often met in modern project management. The problems of this kind refer to the optimal handling of available resources in a candidate project and have emerged, as the result of the even increasing needs of project managers in facing project complexity, controlling related budgeting and finances and managing the construction production line. For the effective resource leveling optimization in problem analysis, evolutionary intelligent methodologies are proposed. Traditional approaches, such as exhaustive or greedy search methodologies, often fail to provide near-optimum solutions in a short amount of time, whereas the proposed intelligent approaches manage to quickly reach high quality near-optimal solutions. In this paper, a new genetic algorithm is proposed for the investigation of the start time of the non-critical activities of a project, in order to optimally allocate its resources. Experiments with small and medium size benchmark problems taken from publicly available project data resources, produce highly accurate resource profiles. The proposed methodology proves capable of coping with larger size project management problems, where conventional techniques like complete enumeration is impossible, obtaining near-optimal solutions.

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Multiple Resources Leveling in Multiple Projects Scheduling Problem Using Particle Swarm Optimization

Cited by 7 publications

References 2 publications

Robust forensic-based investigation algorithm for resource leveling in multiple projects

Robust forensic-based investigation algorithm for resource leveling in multiple projects

Optimizing Multiple-Resources Leveling in Multiple Projects Using Discrete Symbiotic Organisms Search

Application of Evolutionary Algorithms in Project Management

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