A survey of variants and extensions of the resource-constrained project scheduling problem

Hartmann, Sönke; Briskorn, Dirk

doi:10.1016/j.ejor.2009.11.005

Cited by 745 publications

(380 citation statements)

References 191 publications

(290 reference statements)

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“…This is the main reason why researchers try to build methods that give feasible (sub)optimal solution in a time that is acceptable for a user. An agreement is reached in soft computing, where mostly heuristics and metaheuristics (Hartmann and Briskorn 2010;Kolisch and Sprecher 1996) are used.…”

Section: Introductionmentioning

confidence: 99%

iMOPSE: a library for bicriteria optimization in Multi-Skill Resource-Constrained Project Scheduling Problem

et al. 2018

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This paper presents a software library as a research and educational tool for Multi-Skill Resource-Constrained Scheduling Problem. The following useful tools have been implemented in Java: instance Generator, solution validator, solution visualizer and example solvers: Greedy algorithm and Genetic Algorithm. All tools are supported by iMOPSE dataset which consists of 36 instances and additional 'small' 6 instances for educational purpose. In the paper, three test studies are described: (1) educational use of 6 'small' instances, (2) optimization of cost or duration of a schedule, and (3) simple bicritieria optimization of cost/duration of a final schedule. All described tools/examples are freely published on iMOPSE homepage.

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Section: Introductionmentioning

confidence: 99%

iMOPSE: a library for bicriteria optimization in Multi-Skill Resource-Constrained Project Scheduling Problem

et al. 2018

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“…The contractor either receives a bonus for early activity (milestone) completion, or is charged with a penalty for a delay. A review of project scheduling research taking into account economic criteria and cash flows can be found in analytical papers (Hartmann & Briskorn, 2012;Herroelen et al, 1997;Kolisch & Padman, 2001;Węglarz, 1999). Those papers also address other issues which are not discussed here.…”

Section: Introductionmentioning

confidence: 99%

“…Russell (1970) was the first to develop a model (the Max-NPV model) in which the discounted cash flows generated during project execution were optimised. NPV is the most common economic assessment criterion for project scheduling (Hartmann & Briskorn, 2012).…”

Section: Introductionmentioning

confidence: 99%

A Two-Phase Algorithm for a Resource Constrained Project Scheduling Problem with Discounted Cash Flows

Klimek

Łebkowski

2013

DMMS

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Abstract. This paper presents a Resource-Constrained Project Scheduling Problem (RCPSP) settled by contractual milestones. The criterion analysed here is the maximisation of aggregate discounted cash flows from the contractor's perspective, known as an RCPSP problem with Discounted Cash Flows (RCPSPDCF). The cash flows analysed here cover the contractor's cash outflows (negative cash flows), related to the commencement of individual activities, and cash inflows (positive cash flows) after the fulfilment of individual milestones. The authors propose a two-phase algorithm for solving the problem defined. In the first phase, the simulated annealing metaheuristics is used, designed to identify a forward schedule with as high total DCF as possible. In the second phase, the best first-phase schedule is improved by right shifts of activities. To this end, the procedure which iteratively shifts tasks by one unit is applied, with a view to maximising the objective function. Activity shifts take into consideration precedence and resource constraints, and they are performed for a specified resource allocation to activities. This paper also includes an analysis of the problem for a sample project. The results of computational experiments are then analysed. The experiments were run with the use of standard test problems from the Project Scheduling Problem LIBrary (PSPLIB), with additionally defined cash flows and contractual milestones.

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“…[3][12] [8]) as extension of RCPSP [4]. It is NP-hard [2] and there is no effective algorithm to solve it.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, several types of (meta)heuristic methods can be effectively applied. There can be found applications of (MS-)RCPSP in literature based on: heuristics [3] [12], tabu search [11], evolutionary algorithms (EA) with specialized operators [10], (hybridized) ant colony optimization [9], teaching-learningbased optimization algorithm [13], differential evolution [14], hybridized differential evolution [6] and many others.…”

Section: Introductionmentioning

confidence: 99%

Co-Evolutionary Algorithm solving Multi-Skill Resource-Constrained Project Scheduling Problem

Myszkowski¹,

Laszczyk²,

Kalinowski³

2017

Annals of Computer Science and Information Systems

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Abstract-This paper presents methods solving MS-RCPSP as a main task-resource-time assignment optimization problem. In the paper there are presented four variants of Evolutionary Algorithm applied to MS-RCPSP problem: concerning prioritization the tasks (or resources), combined task-resources prioritizing approach and co-evolution based approach that effectively solves problem dividing it to two subproblems. All approaches are examined using benchmark MS-RCPSP iMOPSE dataset and results show that the problem decomposition is effective. All experiments are described, statistically verified and summarized. Conclusions and promising areas of future work are presented.

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A survey of variants and extensions of the resource-constrained project scheduling problem

Cited by 745 publications

References 191 publications

iMOPSE: a library for bicriteria optimization in Multi-Skill Resource-Constrained Project Scheduling Problem

iMOPSE: a library for bicriteria optimization in Multi-Skill Resource-Constrained Project Scheduling Problem

A Two-Phase Algorithm for a Resource Constrained Project Scheduling Problem with Discounted Cash Flows

Co-Evolutionary Algorithm solving Multi-Skill Resource-Constrained Project Scheduling Problem

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