Extending the Multimode Resource-Constrained Project Scheduling Problem by Including Value Considerations

Balouka, Noemie; Cohen, Ignacio Sánchez; Shtub, Avraham

doi:10.1109/tem.2015.2497209

Cited by 16 publications

(21 citation statements)

References 34 publications

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“…MRCPSP mainly studies how to arrange the execution mode and start time of each activity based on the project activity network diagram to meet the constraints on resources and activity sequence, to make the project schedule shortest. Its essence is to find the best combination of each activity execution mode and start time [13] . Compared with the singlemode scheduling problem, MRCPSP, which is under resource constraints, not only need to select the execution mode of each activity in the project, but also need to determine the start-up period of the activity.…”

Section: Rcpsp (Resource-constrained Project Schedulingmentioning

confidence: 99%

“…Meaning of the above constraints: formula (9) represents the start time of the project is 0; Constraint (10) indicates that each task can only be implemented in one mode; constraint (11) restricts the logical relationship of various activities in the project, that is to say, the subsequent activities can only be started after the execution of the front-end activities; Constraint condition (12) is to constrain the resources of the problem, that is, the sum of all the demands for resource k in the execution activities at time t shall not exceed its upper limit, where at represents the task being executed At time t; Constraint (13) indicates that the sequence between the import node and the corresponding critical activity remains unchanged after the import buffer is added. NCij represents the corresponding non-critical chain, i is the chain tail task of the non-critical chain NCij, j is the task on the critical chain CC, and i is the immediate task of j.…”

Section: Figure 7 Ccm Scheduling Network Diagrammentioning

confidence: 99%

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Complex Equipment Remanufacturing Schedule Management Based on Multi-Layer Graphic Evaluation and Review Technique Network and Critical Chain Method

Zhang

Liu

2020

IEEE Access

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In order to solve the problem of project schedule delays caused by resource conflicts and uncertainty of the environment, work duration, and logical relationship, this paper proposed CCPSP (critical chain project scheduling problem) optimal scheduling model which integrates CCM (critical chain method) and multi-level GERT (graphical evaluation and review technique) network. DEACA (differential evolution ant colony algorithm) is designed to solve the problem, in which DE (differential evolution algorithm) is used to deal with the cross problem and mutation problem, and ACA (ant colony algorithm) is used to deal with each stage of the optimization process. The activity resource list is used as the coding rule of each feasible scheduling solution. The activity resource list is used as the coding rule of every feasible scheduling solution, and the activity list is generated by roulette using pheromone and heuristics. Insert and swap neighborhood search structures are introduced to optimize the solution iteratively, and the Pareto file is used to save the non-dominated solution, which is updated in each generation of ant colony search. This paper makes full use of the advantages of the two algorithms to achieve fast convergence and a global search for optimal solutions. At the same time of seeking the optimization algorithm, considering the multiresource constraints, environmental uncertainties and other factors of the project, a buffer is set up, and a "minimum duration-maximum robustness" project schedule is formulated. Finally, through the analysis and verification of the project example, it shows that the project schedule made by this method is feasible. INDEX TERMS GERTs (graphic evaluation and review technique simulation), CCM (critical chain method), CCPSP (critical chain project scheduling problem), Schedule plan, DEACA (Differential Evolution Ant Colony Algorithm), schedule buffer

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Section: Rcpsp (Resource-constrained Project Schedulingmentioning

confidence: 99%

Section: Figure 7 Ccm Scheduling Network Diagrammentioning

confidence: 99%

Complex Equipment Remanufacturing Schedule Management Based on Multi-Layer Graphic Evaluation and Review Technique Network and Critical Chain Method

Zhang

Liu

2020

IEEE Access

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“…The majority of research eforts related to RCPSP assume complete information about the scheduling problem to be solved and a static and deterministic environment within which the precomputed baseline schedule is executed [6]. However, in the real world, project activities are subject to considerable uncertainties, stemming from various sources, which are gradually resolved during project execution.…”

Section: The Main Efects Of the Uncertainties In Project Schedulingmentioning

confidence: 99%

“…These uncertainties may be due to diferent sources, such as estimation errors, late delivery of resources, unforeseen weather conditions, unpredictable incidents (machine or worker) and others [6].…”

Section: Stochastic Scheduling Approachmentioning

confidence: 99%

Kinematic Model for Project Scheduling with Constrained Resources Under Uncertainties

Garbi¹,

Grandinetti²

2017

Kinematics

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Project management practitioners and researchers recognize that the project scheduling eforts are made based on information with many uncertainties and in an environment with constrained resources. This chapter presents the kinematic model named as Coupled Estimate Technique for project scheduling with constrained resources under uncertainties. The Coupled Estimate Technique provides tools of analytical analysis, given that the modelled duration depends on the planned duration and on the resource variability (aleatory uncertainty), as well as the modelled resource depends on the planned resource and on the duration variability (aleatory uncertainty), and also provides tools of graphical analysis, given that the durations and resources of activities, work packages or phases of the project are represented in the bidimensional graphics. In developing the mathematical formulation of the Coupled Estimate Technique, the project precedence diagram was considered as a kinematic chain of robotic manipulators, which may be in chain coniguration open (serial), closed (parallel) and/or hybrid. This chapter describes the resource-constrained project scheduling problem (RCPSP) under uncertainties, identiies the limitations and opportunities in the previous work on planning under uncertainties and presents the fundamentals and method of the kinematic model for project scheduling with constrained resources under uncertainties along with a short example of implementation.

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“…It is different from the sequence independent which depends only on the job to be processed [2,3]. Meanwhile, the setup time is regarded as negligible in a lot of cases thus it is often ignored or dealt with a part of processing time [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion

Wang

2017

Sustainability

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This paper focuses on the flowshop scheduling problem with sequence dependent setup times (FSSP-SDST), which has been an investigated object for decades as one of the most popular scheduling problems in manufacturing systems. A novel hybrid local search algorithm called HLS is presented to solve the flowshop scheduling problem with sequence dependent setup times with the criterion of minimizing the makespan. Firstly, the population is initialized by the Nawaz-Enscore-Hoam based problem-specific method (NEHBPS) to generate high quality individuals of the current population. Then, a global search embedded with a light perturbation is designed to produce a new population. After that, to improve the quality of individuals in the current population, a single insertion-based local search is applied. Meanwhile, a further local search strategy based on the insertion-based local search is used to find better solutions for the individuals which are non-improved. Finally, the heavy perturbation is used to explore potential solutions in the neighbor region. To validate the performance of HLS, we compare our proposed algorithm with other competitive algorithms on Taillard benchmark problems. From the experimental results, it can be concluded that the proposed algorithm outperforms the benchmark algorithms.

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Extending the Multimode Resource-Constrained Project Scheduling Problem by Including Value Considerations

Cited by 16 publications

References 34 publications

Complex Equipment Remanufacturing Schedule Management Based on Multi-Layer Graphic Evaluation and Review Technique Network and Critical Chain Method

Complex Equipment Remanufacturing Schedule Management Based on Multi-Layer Graphic Evaluation and Review Technique Network and Critical Chain Method

Kinematic Model for Project Scheduling with Constrained Resources Under Uncertainties

A Hybrid Local Search Algorithm for the Sequence Dependent Setup Times Flowshop Scheduling Problem with Makespan Criterion

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