Academic literature on the topic 'Resource and time constrained multi-project scheduling problem'
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Journal articles on the topic "Resource and time constrained multi-project scheduling problem"
Suresh, M., Pankaj Dutta, and Karuna Jain. "Resource Constrained Multi-Project Scheduling Problem with Resource Transfer Times." Asia-Pacific Journal of Operational Research 32, no. 06 (2015): 1550048. http://dx.doi.org/10.1142/s0217595915500487.
Full textAltintas, Cansu, and Meral Azizoglu. "A Resource Constrained Project Scheduling Problem With Multi-Modes." International Journal of Information Technology Project Management 11, no. 1 (2020): 55–70. http://dx.doi.org/10.4018/ijitpm.2020010104.
Full textKannimuthu, Marimuthu, Benny Raphael, Palaneeswaran Ekambaram, and Ananthanarayanan Kuppuswamy. "Comparing optimization modeling approaches for the multi-mode resource-constrained multi-project scheduling problem." Engineering, Construction and Architectural Management 27, no. 4 (2019): 893–916. http://dx.doi.org/10.1108/ecam-03-2019-0156.
Full textWang, Ru, and Jing Lian. "Research on Construction Schedule Optimization of Assembly Building Based on NSGA-II." E3S Web of Conferences 165 (2020): 06055. http://dx.doi.org/10.1051/e3sconf/202016506055.
Full textKong, Feng, and Dong Dou. "Resource-Constrained Project Scheduling Problem under Multiple Time Constraints." Journal of Construction Engineering and Management 147, no. 2 (2021): 04020170. http://dx.doi.org/10.1061/(asce)co.1943-7862.0001990.
Full textGhamginzadeh, Arman, Amir Abbas Najafi, and Mohammad Khalilzadeh. "Multi-Objective Multi-Skill Resource-Constrained Project Scheduling Problem Under Time Uncertainty." International Journal of Fuzzy Systems 23, no. 2 (2021): 518–34. http://dx.doi.org/10.1007/s40815-020-00984-w.
Full textDang Quoc, Huu, Loc Nguyen The, Cuong Nguyen Doan, and Toan Phan Thanh. "A NEW ALGORITHM FOR MULTI-SKILL RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM BASED ON CUCKOO SEARCH STRATEGY." Journal of Science Natural Science 65, no. 6 (2020): 98–109. http://dx.doi.org/10.18173/2354-1059.2020-0034.
Full textChen, James C., Wun Hao Jaong, Cheng Ju Sun, Hung Yu Lee, Jenn Sheng Wu, and Chung Chao Ku. "Applying Genetic Algorithm to Resource Constrained Multi-Project Scheduling Problems." Key Engineering Materials 419-420 (October 2009): 633–36. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.633.
Full textTosselli, Laura, Verónica Bogado, and Ernesto Martínez. "Multi-agent Learning by Trial and Error for Resource Leveling during Multi-Project (Re)scheduling." Journal of Computer Science and Technology 18, no. 02 (2018): e14. http://dx.doi.org/10.24215/16666038.18.e14.
Full textColak, Selcuk, Anurag Agarwal, and Selcuk Erenguc. "Multi-Mode Resource-Constrained Project-Scheduling Problem With Renewable Resources: New Solution Approaches." Journal of Business & Economics Research (JBER) 11, no. 11 (2013): 455. http://dx.doi.org/10.19030/jber.v11i11.8193.
Full textDissertations / Theses on the topic "Resource and time constrained multi-project scheduling problem"
Gholizadeh, Tayyar Shadan. "An optimization-based framework for concurrent planning of multiple projects and supply chain : application on building thermal renovation projects." Thesis, Ecole nationale des Mines d'Albi-Carmaux, 2017. http://www.theses.fr/2017EMAC0006/document.
Full textThe application context of the current study is on a CRIBA project. The CRIBA aims to industrialize an integrated solution for the insulation and thermal renovation of building complexes in France. As a result, a significant part of the added value is transferred from the renovation sites to the manufacturing centers, making both synchronized. Planning is one of the important steps in project management. Depending on the different viewpoints of organizations, successful planning for projects can be achieved by performing to optimality within the time, cost, quality factors as well as the efficient assignment of resources. Planning for the allocation of resources becomes more complex when a set of projects is sharing renewable and non-renewable resources. The global objective of the study is to develop a decision-making tool for decision-makers to plan multiple projects by integrating the allocation of the renewable resources and planning the flow of non-renewable resources to the project worksites. In this context, non-renewable resources such as equipment and labor have a limited initial availability at the construction sites. Nevertheless, we assume that additional limited amounts can be added to the projects. In addition, we take into account the interest of the project coordinators in supplying the non-renewable resources in a just-in-time manner to the projects, especially for low-demand resources with a high price. This requires extending the framework of the project planning by including the planning of the supply chain which is responsible. Finally, in order to meet the requirements for environmentally responsible decision-making, the model envisages the transportation and recycling of waste from project sites to appropriate centers. A mixed integer linear model of the problem is proposed. Since it falls within the class of NP-hard optimization models, a double resolution is targeted: first, using a solver and then a metaheuristic based on the genetic algorithm. In addition, in order to facilitate the use of the model by users unfamiliar with operational research, a web-based decision-making support system has been developed. All the contributions are evaluated in a set of case studies from the CRIBA project
Bettemir, Onder Halis. "Optimization Of Time-cost-resource Trade-off Problems In Project Scheduling Using Meta-heuristic Algorithms." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611971/index.pdf.
Full textgenetic algorithm, genetic algorithm with simulated annealing, hybrid genetic algorithm with simulated annealing and particle swarm optimization meta-heuristic algorithms are implemented. The algorithms are tested by using the project sets of Kolisch and Sprecher (1996). Genetic algorithm with simulated annealing and hybrid genetic algorithm simulated annealing algorithm obtained very successful results when compared with the previous state of the art algorithms. 120-activity multi-mode problem set is produced by using the single mode problem set of Kolisch and Sprecher (1996) for the analysis of resource constrained time cost trade-off problem. Genetic algorithm with simulated annealing presented the least total project cost.
Meng-FangWu and 吳孟舫. "Multi-mode resources-constrained project scheduling problem with activity waiting time." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/99662373039126789705.
Full text國立成功大學
工業與資訊管理學系碩博士班
100
To make the project scheduling problem close to realistic situation, multi-mode resources-constrained project scheduling problem (MRCPSP) is extend from the resources constrained project scheduling problem (RCPSP). During the implementation of projects, there are some waiting time limitations between activities. Although the waiting time won’t increase activity processes time directly and consume any renewable resources as well as nonrenewable resources, it affects the starting time of the direct follow-up activity and the total project makespan. This study use a genetic algorithm to solve the problems of MRCPSP with waiting time limitations, and to minimize total project makespan. The dataset are selected from project scheduling problem library (PSPLIB). This study considered two limitations: First, randomly selected activities would be considered with the waiting time limitations. Second, there was different waiting time corresponding to each mode. Furthermore, this study try to explore the effects of schedules by examining different sizes project problems with activity waiting time. First of all, we use the proposed algorithm to find the mutation probability for different sizes of project problems. Then, we find the feasible solution by using different crossover methods, and compare the feasible solution. The results showed that the two-point crossover can get a better feasible solution, and one-point crossover can get a feasible solution in a shorter time.
Wei, Ru-san, and 魏汝珊. "The Research of Multi-mode Resource Constrained Project Scheduling Problem in Stochastic Working Time." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/72145782188548163404.
Full text國立中央大學
土木工程研究所
100
Due to the fast development of global economy, project scheduling is more and more important. Because the project size grows rapidly nowadays, the project scheduling problem is much more complex than before. Traditionally, the critical path method (CPM) and the program evaluation and review technique (PERT) were used to formulate the project scheduling problems. The past time-controlled process for CPM and PERT is neither efficient nor effective from a system perspective, especially due to the short of environment resources recently. Considering of the resource finite and cash flow, resource constrained project scheduling problem (RCPSP), multi-mode resource constrained project scheduling problem (MRCPSP) and multi-mode resource constrained project scheduling problem with discounted cash flow (MRCPSPDCF) are researched in many years. Not only sources and money but stochastic disturbances arising from variations in working time in actual operations should be noticed. The past researches on the project scheduling is mainly based on the average working time, which do not consider the stochastic working time. Therefore, when actual project scheduling is affected by stochastic working time, the already planned project scheduling will be disturbed and lose its system optimization. Dealing with the multi-mode resource constrained project scheduling problem with discounted cash flow (MRCPSPDCF), this research adopts the time-precedence network technique to formulate a stochastic project scheduling model which considers the cash flow value of time and related operating and resource constraints. The model is formulated as an integer network flow problem with side constraints, which is characterized as NP-hard in terms of optimization. We employ the CPLEX mathematical programming solver to solve the problem. Otherwise we do the numerical tests to evaluate the performance of the proposed model, and the data comes from Project Scheduling Problem Library (PSPLIB).Performing sensitive and scenario analysis for different parameters, and the test results show the model to be good and that the solution method could be useful in practice. At last, conclusions and suggestions are given.
Nudtasomboon, Nudtapon. "Methodology for the multi-objective, resource-constrained project scheduling problem." Thesis, 1993. http://hdl.handle.net/1957/35939.
Full textGraduation date: 1993
Chen, Tai-Lin, and 陳泰霖. "Floating Time Consumption Impacts On Multi-Project Resource Constrained Scheduling." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/40143395770738407012.
Full text國立屏東科技大學
工業管理系所
100
Float time is job’s buffer for project scheduling. If using float is hardly, schedule completion time can delay and cost can loss hard. Most project schedule research focuses on minimize completion time or minimize total cost, the few studies on floating consume affect the project schedule. So this study develops a new Critical Path Method(CPM) for calculating the correct float time, to avoid using errors float time, and reducing impact for completion time. This study applied Ant Colony Optimization (ACO) to establish the best combination and develop resource constraints scheduling model to achieve the resource allocation optimization and the shortest finishing time of a project under resource constraints and the sequence for project activities. Finally, the case of empirical scheduling model efficiency, and calculate the correct float information, reducing the error of the float.
Song, Jin-Ru, and 宋瑾茹. "A Study on the Robust Resource-Constrained Multi-Project Scheduling Problem." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/64929523114990587107.
Full text國立屏東科技大學
工業管理系所
96
The main purpose of this study is to investigate a bi-objective resource-constrained multi-project scheduling problem. Two objectives are considered: net present value (NPV) maximization and robustness maximization. A mixed integer nonlinear programming (MINLP) model and a particle swarm optimization (PSO) algorithm are presented to solve the bi-objective resource-constrained multi-project scheduling problem. The effectiveness of the proposed PSO algorithm will be demonstrated by comparing it with the MINLP model and some existing rules. The results indicate that the solution obtained by the PSO algorithm is very close to the optimal solution, and that the proposed PSO algorithm does not consume much computational time. In addition, the results indicate that the PSO algorithm is superior to the existing heuristic rules under the performance criteria of the project NPV and the schedule robustness. The approaches presented in this study could provide project managers with useful tools for making better decisions.
Buddhakulsomsiri, Jirachai. "Multi-mode resource-constrained project scheduling problem with resource vacations and task splitting." Thesis, 2003. http://hdl.handle.net/1957/31495.
Full textGraduation date: 2003
Lo, Chiao-Yu, and 駱巧瑜. "Solving the Multi-mode Resource-constrained Multi-project Scheduling Problem by Bi-level Programming." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/42309930614264632884.
Full text淡江大學
資訊管理學系碩士班
102
In practice, project management is often performed in a multi-project context, where individual projects compete for source resources. Moreover, the activities in a project could be accomplished in one out of several execution modes, in which, each execution mode represents an alternative combination of resource requirement of the activity and its duration. This study aims to deal with such a multi-project, multi-mode, and resource-constrained project scheduling problem. Previous studies on multi-project scheduling problems generally assumed that resources can be shared among projects, and thus, the multiple projects can be combined into a single project, and solved by available algorithms that are formulated for single project scheduling. The present study considers a different case where resources cannot be shared among projects and hence the resources need to be allocated to individual projects; after the resources are allocated to each project, the project manager of each project faces a typical multi-mode resource constrained project scheduling problem. Owing to the above hierarchical decision-making structure, this study suggests using the bi-level decentralized programming to model the problem. The resources used in a project in fact is a combination of various resources. Thus, it is ideal to allocate resources to projects in a combinatorial manner. Combinatorial auction is suitable for dealing with such a problem. In the combinatorial action mechanism considered in this study, upper-level decision-maker is the auctioneer and the project managers at the low-level are bidders. Project managers submit bids, which are in the form of resource combination and are obtained by solving a least-cost multi-mode resource-constrained projects scheduling problem, to the upper-level decision-maker. After receiving all bids from project managers, the upper-level decision-maker solves a winner determination problem to determine the winning bids which represent the result of the resource allocation decision. In addition to the regular combinatorial auction model, this study proposes a fuzzy combinatorial auction model to deal with the situation where the resources are not enough to complete projects by their due dates. The solution of the fuzzy combinatorial auction model shows the trade-off between resource expansion and tardiness improvement. The proposed solution procedure is programmed by JAVA with CPLEX library, and uses problem instances of Besikci et al. (2013) to evaluate the performance of the proposed approach. The results show the solutions of our approach not only able to compete with that of literature, and outperform the literature in computation times.
Chien, Ming Tu, and 錢明淦. "A Genetic Algorithms for the Resource Constrained Project Scheduling Problem with Multi-Mode." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/14949490672869325225.
Full text元智大學
工業工程研究所
87
The purport of this article is to develop the heuristic algorithm, which is applicable in the multi-mode and the project scheduling problem of resource constrained, so as to shorten the construction time of the project as much as possible. The developed heuristic algorithm is based on genetic algorithms. We submitted two special encoding technologies to match with appropriate project scheduling so that the problem of illegal offspring could be avoided. Meanwhile, we introduced the idea of using the immigration operator and dynamic and adaptive strategies for varying the control parameters to strengthen the searching ability of algorithms. In addition, we also attempted several ways in crossover and mutation. Regarding setting of the parameters in algorithms, different parameters in this article was designed according to the Taguchi’s experiment in order to find out the most stable and suitable parameters set. In this article, Turbo C 2.0 was used to write programs. In order to compare with the effectiveness of algorithms designed by other international researchers, this program was tested by sample test in the PSPLIB. The result was perfect and superior to other researches’, such as average error, standard average error or the numbers of the best solution. In addition, we set up a website concerning the problem of case managing. Those who are interested in this project can down load the important references. This website also provides linkage to different sample tests. The address of this website is http://project.engineer.com.tw.
Books on the topic "Resource and time constrained multi-project scheduling problem"
Franck, Birger. Resource-constrained project scheduling problem with time windows: Structural questions and priority-rule methods. Universität Karlsruhe, 1998.
Nudtasomboon, Nudtapon. Methodology for the multi-objective, resource-constrained project scheduling problem. 1993.
A Decomposition Approach for the Multi-Modal, Resource-Constrained, Multi-Project Scheduling Problem with Generalized Precedence and Expediting Resources. Storming Media, 2001.
Book chapters on the topic "Resource and time constrained multi-project scheduling problem"
Jędrzejowicz, Piotr, and Aleksander Skakovski. "A Cross-Entropy Based Population Learning Algorithm for Multi-mode Resource-Constrained Project Scheduling Problem with Minimum and Maximum Time Lags." In Computational Collective Intelligence. Technologies and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16693-8_40.
Full textSaeidi, Arman, Kamran Rezaie, Alireza Nazari, and Amir Hossein Ordibazar. "Proposing a Pre-emptive Resource Constrained Project Scheduling Problem (PRCPSP) Model to Optimize Manpower and Project Delivery Time (A Case Study)." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62784-3_40.
Full textCoelho, José, and Mario Vanhoucke. "The Multi-Mode Resource-Constrained Project Scheduling Problem." In Handbook on Project Management and Scheduling Vol.1. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05443-8_22.
Full textYaghoubi, Saeed, Siamak Noori, and Amir Azaron. "The Markovian Multi-Criteria Multi-Project Resource-Constrained Project Scheduling Problem." In Handbook on Project Management and Scheduling Vol. 2. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05915-0_8.
Full textJedrzejowicz, Piotr, and Ewa Ratajczak-Ropel. "A-Team Solving Distributed Resource-Constrained Multi-project Scheduling Problem." In Computational Collective Intelligence. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98446-9_23.
Full textMyszkowski, Paweł B., and Jȩdrzej J. Siemieński. "GRASP Applied to Multi–Skill Resource–Constrained Project Scheduling Problem." In Computational Collective Intelligence. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45243-2_37.
Full textZhou, Rong, Chun-ming Ye, and Hui-min Ma. "Model Research of Multi-Objective and Resource-Constrained Project Scheduling Problem." In The 19th International Conference on Industrial Engineering and Engineering Management. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38427-1_104.
Full textPamay, M. Berke, Kerem Bülbül, and Gündüz Ulusoy. "Dynamic Resource Constrained Multi-Project Scheduling Problem with Weighted Earliness/Tardiness Costs." In International Series in Operations Research & Management Science. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-9056-2_10.
Full textSerafini, P., and M. G. Speranza. "A Multi-Stage Decomposition Approach for a Resource Constrained Project Scheduling Problem." In Methodology, Implementation and Applications of Decision Support Systems. Springer Vienna, 1991. http://dx.doi.org/10.1007/978-3-7091-2606-6_9.
Full textStürck, Christian, and Patrick Gerhards. "Providing Lower Bounds for the Multi-Mode Resource-Constrained Project Scheduling Problem." In Operations Research Proceedings 2016. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55702-1_73.
Full textConference papers on the topic "Resource and time constrained multi-project scheduling problem"
Liu, Wenjian, and Jinghua Li. "Development of Hybrid Genetic Algorithms for the Resource Constrained Multi-Project Scheduling Problem." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85721.
Full textCai, Zhicheng, and Xiaoping Li. "A hybrid genetic algorithm for resource-constrained multi-project scheduling problem with resource transfer time." In 2012 IEEE International Conference on Automation Science and Engineering (CASE 2012). IEEE, 2012. http://dx.doi.org/10.1109/coase.2012.6386457.
Full textGnagi, M., T. Rihm, and N. Trautmann. "A Continuous-Time MILP Formulation for the Multi-Mode Resource-Constrained Project Scheduling Problem." In 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2018. http://dx.doi.org/10.1109/ieem.2018.8607285.
Full textOzturk, Guler, and Adalet Oner. "Continuous Time MILP Models for Multi-Mode Resource Constrained Project Scheduling Problems." In 2020 9th International Conference on Industrial Technology and Management (ICITM). IEEE, 2020. http://dx.doi.org/10.1109/icitm48982.2020.9080355.
Full textZhang, Jing-wen, and Hui-fang Shan. "Multi-Mode Double Resource-Constrained Time/Cost Trade-Offs Project Scheduling Problems." In 2009 International Conference on Management and Service Science (MASS). IEEE, 2009. http://dx.doi.org/10.1109/icmss.2009.5302886.
Full textGnagi, M., and N. Trautmann. "A Continuous-Time Mixed-Binary Linear Programming Formulation for the Multi-Site Resource-Constrained Project Scheduling Problem." In 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2019. http://dx.doi.org/10.1109/ieem44572.2019.8978811.
Full textCai, Junqi, and Zhihong Peng. "A Heuristic Algorithm for Solving Resource Constrained Project Scheduling Problem with Transfer Time under Resource Bundle." In 2019 Chinese Control Conference (CCC). IEEE, 2019. http://dx.doi.org/10.23919/chicc.2019.8865803.
Full textBofill, Miquel, Jordi Coll, Josep Suy, and Mateu Villaret. "Compact MDDs for Pseudo-Boolean Constraints with At-Most-One Relations in Resource-Constrained Scheduling Problems." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/78.
Full textGnagi, M., A. Zimmermann, and N. Trautmann. "A Continuous-Time Unit-Based MILP Formulation for the Resource-Constrained Project Scheduling Problem." In 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2018. http://dx.doi.org/10.1109/ieem.2018.8607337.
Full textRihm, Tom, and Norbert Trautmann. "An assignment-based continuous-time MILP model for the resource-constrained project scheduling problem." In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2017. http://dx.doi.org/10.1109/ieem.2017.8289846.
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