A preemptive bound for the Resource Constrained Project Scheduling Problem

Haouari, Mohamed; Kooli, Anis; Néron, Emmanuel; Carlier, Jacques

doi:10.1007/s10951-013-0354-9

Cited by 11 publications

(7 citation statements)

References 23 publications

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“…As a consequence of Proposition 5, we can solve the LPrelaxation of IEE by the much more compact LPGS model. Carlier and Néron (2003) and Haouari et al (2014) also propose many additional cutting planes for LPGS. An interesting future research direction is to solve such a stronger version of LPGS as an LP subroutine in combination with a branching rule on the original IEE model.…”

Section: Proposition 4 [Split Property]mentioning

confidence: 99%

A polyhedral study of event-based models for the resource-constrained project scheduling problem

Tesch

2020

J Sched

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In this paper, we study event-based mixed-integer programming (MIP) formulations for the resource-constrained project scheduling problem (RCPSP) that represent an alternative to the more common time-indexed model (DDT) (Pritsker et al. in Manag Sci 16(1):93-108, 1969; Christofides et al. in Eur J Oper Res 29(3):262-273, 1987) for the case when the scheduling horizon is large. In contrast to time-indexed models, the size of event-based models does not depend on the time horizon. For two event-based models OOE and SEE introduced by Koné et al. (Comput Oper Res 38(1):3-13, 2011), we first present new valid inequalities that strengthen the original formulation. Furthermore, we state a new event-based model, the Interval Event-Based Model (IEE), and deduce natural linear transformations between all three models. Those transformations yield the strict domination order I E E S E E O O E for their respective linear programming relaxations, meaning that the new IEE model has the strongest linear relaxation among all known event-based models. In addition, we show that DDT can be retrieved from IEE by subsequent expansion and projection of the underlying solution space. This yields a unified polyhedral view on a complete branch of MIP models for the RCPSP. Finally, we also compare the computational performance between all models on common test instances of the PSPLIB (Kolisch and Sprecher in Eur J Oper Res 96(1):205-216, 1997).

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Section: Proposition 4 [Split Property]mentioning

confidence: 99%

A polyhedral study of event-based models for the resource-constrained project scheduling problem

Tesch

2020

J Sched

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“…Peng and Huang [14] worked on resource constrained scheduling problem where the specific part of study was pre-emptive bound. A new approach of destructive lower bound for NP-hard problem is proposed.…”

Section: Background and Related Workmentioning

confidence: 99%

“…The results gathered from these tests showed that the approach is more adaptive and provides the excellent scheduling results while outperforming many other algorithms. Performance improvement is reported using the 5 best lower bounds of instances [14]. The study focused on specific types of instances of PSLIB.…”

Section: Background and Related Workmentioning

confidence: 99%

Novel Approach to Solve Resource Constrained Project Scheduling Problem (RCPSP)

Alhumrani¹,

Qureshi

2016

IJMECS

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In this paper, resource constrained project scheduling problem is taken and solved using genetic algorithm. This algorithm solves the problem as a whole in software development, with the limited resource the project has to be scheduled to the team members. The main aim is to schedule and optimize the resource to complete the project within time. Due to resource constraint environment, the complexity of solving the algorithm increases exponentially. So the traditional methods are not suitable to solve the resource constraint problem. The Genetic Algorithm is taken to solve the multiple resource constraints project scheduling needs. This typical NP-hard problem is solved via mathematical model via genetic algorithm. Software development projects were considered to be resource constrained and project scheduling solution makes the algorithm time efficient.

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“…We refer to the surveys published by Kolisch and Padman [15], Brucker et al [7], Herroelen and Leus [13], Hartmann and Briskorn [12]. The very recent work of Haouari et al [11] uses an LP model based on PRCPSP to compute lower bound for the RCPSP. Also, Schutt et al [23] propose an effective algorithm for RCPSP based on Constraint Programming that allows many open instances to be closed and the lower bounds for RCPSP to be improved.…”

Section: Accepted Manuscriptmentioning

confidence: 99%