A hybrid genetic algorithm for the resource-constrained project scheduling problem

Valls, Vicente; Ballestín, Francisco; Quintanilla, Sacramento

doi:10.1016/j.ejor.2006.12.033

Cited by 215 publications

(111 citation statements)

References 35 publications

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“…The right (left) justification of a given activity consists in determining (for that activity) the start time as late (early) as possible, given the ordering and resource constraints. The use of the justification technique enables a new schedule to be found for which activity makespans are no longer than in schedule S, and often shorter (Valls et al, 2005;Valls et al, 2006;Valls et al, 2008).…”

Section: Proposed Insertion Algorithmsmentioning

confidence: 99%

“…The activity list is decoded to an executable schedule with the use of forward SGS procedures. Solutions are then improved with the use of the justification technique (Valls et al, 2005;Valls et al, 2006;Valls et al, 2008), similar to the technique known as forward-backward improvement (Tormos and Lova, 2001;Tormos and Lova, 2003;Goncalves et al, 2011), used in the most-efficient heuristics for the RCPSP.…”

Section: Introductionmentioning

confidence: 99%

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Insertion Algorithms with Justification for Solving the Resource-Constrained Project Scheduling Problem

Klimek¹,

Łebkowski

2016

dmms

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Abstract. The paper presents the resource-constrained project scheduling problem with the makespan minimization criterion. To solve the problem, the authors propose insertion algorithms that generate schedules with the use of forward serial and parallel decoding procedures. Schedules are improved with the use of the double justification by the extremes technique (first right and then left justification). The efficiency of the procedures proposed is tested on standard test problems from the PSPLIB library.

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Section: Proposed Insertion Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Insertion Algorithms with Justification for Solving the Resource-Constrained Project Scheduling Problem

Klimek¹,

Łebkowski

2016

dmms

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“…EA (Hartmann 1998;Valls et al 2001Valls et al , 2008, TS (Thomas et al 1998;Tsai et al 1998;Verhoeven 1998), SA (Bouleimen et al 2003;Das et al 2011) are well explored and widely applied to solve MS-RCPSP. It is worth a mention that ACO is not the only swarm intelligence metaheuristic used in solving (MS-) RCPSP.…”

Section: Related Workmentioning

confidence: 99%

Hybrid ant colony optimization in solving multi-skill resource-constrained project scheduling problem

et al. 2014

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In this paper, hybrid ant colony optimization (HAntCO) approach in solving multi-skill resource-constrained project scheduling problem (MS-RCPSP) has been presented. We have proposed hybrid approach that links classical heuristic priority rules for project scheduling with ant colony optimization (ACO). Furthermore, a novel approach for updating pheromone value has been proposed based on both the best and worst solutions stored by ants. The objective of this paper is to research the usability and robustness of ACO and its hybrids with priority rules in solving MS-RCPSP. Experiments have been performed using artificially created dataset instances based on real-world ones. We published those instances that can be used as a benchmark. Presented results show that ACO-based hybrid method is an efficient approach. More directed search process by hybrids makes this approach more stable and provides mostly better results than classical ACO.

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“…• Crossover operator: The combination of the genes of both parents is done by a two-point crossover operator based on a modified version of the peak crossover operator of Valls et al (2008) that makes use of the resource utilization ratio.…”

Section: Rcpsp Scheduling Stepmentioning

confidence: 99%

The Multi-Mode Resource-Constrained Project Scheduling Problem

Coelho

Vanhoucke

2014

Handbook on Project Management and Scheduling Vol.1

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This chapter reports on a new solution approach for the multi-mode resource-constrained project scheduling problem (MRCPSP, MPS|prec|C max ). This problem type aims at the selection of a single activity mode from a set of available modes in order to construct a precedence and a (renewable and non-renewable) resource-feasible project schedule with a minimal makespan. The problem type is known to be N P-hard and has been solved using various exact as well as (meta-)heuristic procedures. The new algorithm splits the problem type into a mode assignment and a single mode project scheduling step. The mode assignment step is solved by a satisfiability (SAT) problem solver and returns a feasible mode selection to the project scheduling step. The project scheduling step is solved using an efficient meta-heuristic procedure from literature to solve the resourceconstrained project scheduling problem (RCPSP). However, unlike many traditional meta-heuristic methods in literature to solve the MRCPSP, the new approach executes these two steps in one run, relying on a single priority list. Straightforward adaptations to the pure SAT solver by using pseudo boolean non-renewable resource constraints has led to a high quality solution approach in a reasonable computational time. Computational results show that the procedure can report similar or sometimes even better solutions than found by other procedures in literature, although it often requires a higher CPU time.

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A hybrid genetic algorithm for the resource-constrained project scheduling problem

Cited by 215 publications

References 35 publications

Insertion Algorithms with Justification for Solving the Resource-Constrained Project Scheduling Problem

Insertion Algorithms with Justification for Solving the Resource-Constrained Project Scheduling Problem

Hybrid ant colony optimization in solving multi-skill resource-constrained project scheduling problem

The Multi-Mode Resource-Constrained Project Scheduling Problem

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