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Use of float consumption rate in resource leveling of construction projects

Frontiers of Engineering Management 2022年第1期9卷 135-147页

作者： Atilla DAMCI Gul POLAT Firat Dogu AKIN Harun TURKOGLU Department of Civil Engineering Istanbul Technical UniversityIstanbul34469Turkey

The management of resources has been claimed to be as important as scheduling *** in managing resources may bring about severe delays and cost overruns caused by resource shortages in some cases and/or idle resources in ***,resources should be utilized efficiently to prevent project *** leveling is one of the approaches that are used for the management of *** aims to minimize fluctuations,peaks,and valleys in resource utilization without changing the completion time of a project and the number of resources *** the main principle behind traditional resource leveling is achieving an even flow of resources while the original project duration remains unchanged,the literature supports the need to develop an efficient model that discriminates among the activities that are selected for participation in resource *** this purpose,this study has developed a model that considers the float consumption rates of activities in resource *** float consumption rate is the percentage that is set to determine the maximum amount of float which will be consumed to shift the start time of the *** proposed model allows a scheduler to assign float consumption rates to each activity that can be used during the resource leveling *** the required information is inputted,the proposed model automatically changes the required daily resources as it shifts the noncritical activities along their available total float *** proposed model is expected to minimize the likelihood of severe delays and cost *** model is demonstrated by constructing a network and its resource utilization histograms.

关键词： resource management resource leveling float consumption rate scheduling

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A Novel resource-leveling Approach for Prefabricated Construction Project Based on Genetic Algorithm

A Novel Resource-Leveling Approach for Prefabricated Constru...

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第40届中国控制会议

作者： Miao Yu Yang Wang Xiaoqing Xu School of Management Shenyang Jianzhu University

Traditional analytical and heuristic approaches are inefficient and inflexible when solving prefabricated construction resource leveling *** paper used genetic algorithm（GA） to solve the resource leveling between the production and assembly spaces of prefabricated construction,and evaluate the balance of resource utilization efficiency by minimizing resource variance.A case study is employed to investigate the performance of the proposed optimization model in dealing with the resource leveling *** results show that using genetic algorithm to solve the model can achieve resource leveling efficiently.

关键词： resource leveling Prefabricated building Genetic Algorithm

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An extended particle swarm optimization algorithm based on coarse-grained and fine-grained criteria and its application

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Journal of Central South University of Technology 2008年第1期15卷 141-146页

作者：李星梅张立辉乞建勋张素芳 School of Business Administration North China Electric Power University

In order to study the problem that particle swarm optimization (PSO) algorithm can easily trap into local mechanism when analyzing the high dimensional complex optimization problems, the optimization calculation using the information in the iterative process of more particles was analyzed and the optimal system of particle swarm algorithm was improved. The extended particle swarm optimization algorithm (EPSO) was proposed. The coarse-grained and fine-grained criteria that can control the selection were given to ensure the convergence of the algorithm. The two criteria considered the parameter selection mechanism under the situation of random probability. By adopting MATLAB7.1, the extended particle swarm optimization algorithm was demonstrated in the resource leveling of power project scheduling. EPSO was compared with genetic algorithm (GA) and common PSO, the result indicates that the variance of the objective function of resource leveling is decreased by 7.9%, 18.2%, respectively, certifying the effectiveness and stronger global convergence ability of the EPSO.

关键词： particle swarm extended particle swarm optimization algorithm resource leveling

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