A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems

Jarboui, Bassem; Damak, N.; Siarry, Patrick; Rebaï, Ahmed

doi:10.1016/j.amc.2007.04.096

Cited by 244 publications

(122 citation statements)

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“…Moreover, researchers in the past have pointed to the importance of scheduling multiple projects with constrained resources [10,12]. In the recent literature, many techniques and tools have been developed to overcome the problem of multiple projects; examples include baseline scheduling [13], a combinatorial PSO (CPSO) algorithm [14], and the hybrid genetic algorithm with fuzzy logic controller (flc-hGA) [15]. There seems to be little research that investigates the factors that may overcome the problem of multiple projects.…”

mentioning

confidence: 99%

Extended Critical Success Factor Model for Management of Multiple Projects: An Empirical View From Transnet in South Africa

Nethathe

Waveren

Chan

2011

The South African Journal of Industrial Engineering

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mentioning

confidence: 99%

Extended Critical Success Factor Model for Management of Multiple Projects: An Empirical View From Transnet in South Africa

Nethathe

Waveren

Chan

2011

The South African Journal of Industrial Engineering

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“…Although a comparison with the state-of-the-art results is not fair anymore, the table shows that near-optimal solution can be produced with the new procedure under high stop criterion values. (2010) 0.01% 0.09% 0.22% 0.32% 0.42% 0.57% Wang and Fang (2012) 0.12% 0.14% 0.43% 0.59% 0.90% 1.28% Wang and Fang (2011) 0.10% 0.21% 0.46% 0.57% 0.94% 1.39% Elloumi and Fortemps (2010) -v1 0.21% 0.29% 0.77% 0.91% 1.30% 1.62% Elloumi and Fortemps (2010) -v2 0.14% 0.24% 0.80% 1.14% 1.53% 2.09% Lova et al (2009) 0.06% 0.17% 0.32% 0.44% 0.63% 0.87% Jarboui et al (2008) 0.03% 0.09% 0.36% 0.44% 0.89% 1.10% Ranjbar et al (2009) 0.18% 0.65% 0.89% 0.95% 1.21% 1.64% Alcaraz et al (2003) 0.24% 0.73% 1.00% Table 1.4 reports results for the J30 instances as the average deviation from the minimal critical path length under four stop criterion values and compares the results with the procedure of Van Peteghem and Vanhoucke (2010) which is described as the best performing procedure up to today. The results show that the new SAT based procedure is not able to outperform the best performing procedure when the stop criterion is set relatively low.…”

Section: Computational Resultsmentioning

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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“…Figure 2. Defin ition of search in PSO algorith m [25] In [27] in binary optimal problem solution and in order to prevent local optimal algorithm premature convergence, the mutation operator which is used in genetic algorithm (GA ) is co mbined with PSO which substantially imp roves the algorithm efficiency. Despite optimization variab les` not being binary and according to the positive effect of mutation in last researches, this operator is also used in this paper.…”

Section: T T V T C T R P T X T C T R G T X Tmentioning

confidence: 99%

“…Each individual moves in search space with adjustable velocity and keeps the best position gained ever in its memo ry. The best position obtained by all the individuals of the population is transferred between all particles [22][23][24][25][26]. In fact it is supposed that each particle in each mo ment knows about the best position obtained by all the individuals of the population until that mo ment.…”

Section: Objective Functionmentioning

confidence: 99%

Economic Designing of PV/FC/Wind Hybrid System Considering Components Availability

Arabi¹,

Hajibeigy²

2013

IJMECS

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Abstract-This paper presents an Optimizat ion Sizing of a stand-alone PV/FC/Wind Hybrid System (PFWHS) to optimize the sizes of co mponents of PFWHS. Based on PSO algorith m, one optimal sizing method was developed to determine the optimal configuration of system that can achieve the load required power supply probability (Reliab ility) with a minimu m overall cost of energy (OCE).PFW HS costs involve investments, operation and maintenance as well as loss of load costs. The applied wind and radiat ion datasets belong to northwest region (Jolfa, latitude: 38_56, longitude: 45_ 37, altitude: 710, m) of Iran. In this paper the impact of availability of PFWHS co mponents is investigated on optimal sizing. So, to investigating the impact of component availability rate on PFWHS costs and reliability due to failure and repair rate of PFW HS components and uncertainty in wind speed and solar irradiance, t wo scenarios are considered. In first scenario the availab ility of all co mponents is considered 1 and in second scenario isn't considered 1 because of failure and repair rate of co mponents and uncertainty in wind speed and solar irradiance. Obtained results prove that while the overall cost of energy is optimized, the reliability indices are within a satisfactory bound with regard to the reliab ility standards. Also the results indicate that considering co mplete availability of components causes more reliability rate, so to achieve the actual behavior of PFW HS, the rate of co mponents availability must be considered in suitable insight to designer for supply the load.

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A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems

Cited by 244 publications

References 14 publications

Extended Critical Success Factor Model for Management of Multiple Projects: An Empirical View From Transnet in South Africa

Extended Critical Success Factor Model for Management of Multiple Projects: An Empirical View From Transnet in South Africa

The Multi-Mode Resource-Constrained Project Scheduling Problem

Economic Designing of PV/FC/Wind Hybrid System Considering Components Availability

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