A Population-Based Approach to the Resource-Constrained Project Scheduling Problem

Valls, Vicente; Ballestín, Francisco; Quintanilla, Sacramento

doi:10.1023/b:anor.0000039524.09792.c9

Cited by 87 publications

(45 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Solution representation: since delays in sections 4.1 and 4.2 are done according to the order in which activities appear in the PL, we employ the topological order (TO) representation first proposed by Valls et al (2003Valls et al ( , 2004, and used for the RCPSP by Debels et al (2006). The TO representation ensures a precedence feasible ordering of activities and is updated based on actual finish times after the improvement methods discussed in sections 4.2.2 and 4.2.3 have been applied.…”

Section: Metaheuristicsmentioning

confidence: 99%

Capital- and resource-constrained project scheduling with net present value optimization

Leyman

Vanhoucke

2017

European Journal of Operational Research

View full text Add to dashboard Cite

In this paper, we study the capital-constrained project scheduling problem with discounted cash flows (CCPSPDC) and the capital-and resource-constrained project scheduling problem with discounted cash flows (CRCPSPDC). The objective of both problems is to maximize the project net present value (NPV), based on three cash flow models. Both problems include capital constraints, which force the project to always have a positive cash balance. Hence, it is crucial to schedule activities in such an order that sufficient capital is available.The contribution of this paper is threefold. First, we propose three distinct cash flow models, which affect the capital availability during the project. Second, we introduce two new schedulers to improve capital feasibility, one for the CCPSPDC and one for the CRCPSPDC. The schedulers focus on delaying sets of activities, which cause cash outflows to be received at later time instances, in order to reduce capital shortages. Both schedulers are implemented as part of three metaheuristics from literature, in order to compare the metaheuristics' performance. Two penalty functions have been included, one to improve capital feasibility and another to improve deadline feasibility. Third, the proposed procedure has been tested on a large dataset and the added value of the schedulers has been validated. Managerial insights are provided with respect to the impact of key parameters.

show abstract

Section: Metaheuristicsmentioning

confidence: 99%

Capital- and resource-constrained project scheduling with net present value optimization

Leyman

Vanhoucke

2017

European Journal of Operational Research

View full text Add to dashboard Cite

show abstract

“…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

View full text Add to dashboard Cite

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.

show abstract

“…This representation consists of the starting times of the sub-activities with a positive duration in increasing order followed by set of remaining activity modes that are not part of the feasible schedule (i.e. the sub-activities with a duration of zero) and is an extension of the topological order representation of Valls et al (2003Valls et al ( , 2004. Since a feasible project schedule can be uniquely defined by its activity starting times, such an AL can always be constructed.…”

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

View full text Add to dashboard Cite

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.

show abstract

A Population-Based Approach to the Resource-Constrained Project Scheduling Problem

Cited by 87 publications

References 32 publications

Capital- and resource-constrained project scheduling with net present value optimization

Capital- and resource-constrained project scheduling with net present value optimization

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

The Multi-Mode Resource-Constrained Project Scheduling Problem

Contact Info

Product

Resources

About