A metaheuristic solution approach for the time-constrained project scheduling problem

Verbeeck, Cédric; Peteghem, Vincent Van; Vanhoucke, Mario; Vansteenwegen, Pieter; Aghezzaf, El‐Houssaine

doi:10.1007/s00291-016-0458-7

Cited by 10 publications

(4 citation statements)

References 42 publications

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“…Resource leveling is a well studied area of project scheduling, where a number of exact and heuristic methods are proposed for solving it for various objective functions and under various assumptions, see e.g., (Kis, 2005;Neumann and Zimmermann, 2000;Verbeeck et al, 2017). Drótos and Kis (2011) consider a dedicated parallel machine environment, and propose and exact method for solving resource leveling problems optimally with hundreds of jobs.…”

Section: Previous Workmentioning

confidence: 99%

A common approximation framework for early work, late work, and resource leveling problems

Györgyi

Kis

2020

European Journal of Operational Research

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We study the approximability of two related machine scheduling problems. In the late work minimization problem, there are identical parallel machines and the jobs have a common due date. The objective is to minimize the late work , defined as the sum of the portion of the jobs done after the due date. A related problem is the maximization of the early work , defined as the sum of the portion of the jobs done before the due date. We describe a polynomial time approximation scheme for the early work maximization problem, and we extended it to the late work minimization problem after shifting the objective function by a positive value that depends on the problem data. We also prove an inapproximability result for the latter problem if the objective function is shifted by a constant which does not depend on the input. These results remain valid even if the number of the jobs assigned to the same machine is bounded. This leads to an extension of our approximation scheme to some variants of the resource leveling problem, for which no approximation algorithms were known.

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Section: Previous Workmentioning

confidence: 99%

A common approximation framework for early work, late work, and resource leveling problems

Györgyi

Kis

2020

European Journal of Operational Research

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“…The Resource Availability Cost Problem (RACP) minimises the resource availability levels, constant over the planning horizon, for all resources (Möhring, 1984). The Time-Constrained Project Scheduling Problem (TCPSP) differs from the RACP since a fixed resource availability is defined and only a decision is made on hiring extra capacity for a certain resource type, which is budgeted as overtime and temporary resources, in order to complete the project within a specific deadline (Verbeeck et al, 2017).…”

Section: Project Schedulingmentioning

confidence: 99%

A decomposed branch-and-price procedure for integrating demand planning in personnel staffing problems

Eeckhout

Vanhoucke

Maenhout

2020

European Journal of Operational Research

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“…Scheduling problem is complex problem because to get best solution must be balancing allocation the visit that to pass all contrains. The main focus of scheduling is to minimize the total duration of the visit [3]. In addition, the delay of scheduling during change the part is very important because get influence the tota duration of the scheduling [4].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Genetic Algorithms and Simulated Annealing for Multi-trip Vehicle Routing Problem with Time Windows

Ariyani¹,

Mahmudy²,

Anggodo³

2018

IJECE

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Vehicle routing problem with time windows (VRPTW) is one of NP-hard problem. Multi-trip is approach to solve the VRPTW that looking trip scheduling for gets best result. Even though there are various algorithms for the problem, there is opportunity to improve the existing algorithms in order gaining a better result. In this research, genetic algoritm is hybridized with simulated annealing algoritm to solve the problem. Genetic algoritm is employed to explore global search area and simulated annealing is employed to exploit local search area. Four combination types of genetic algorithm and simulated annealing (GA-SA) are tested to get the best solution. The computational experiment shows that GA-SA1 and GA-SA4 can produced the most optimal fitness average values with each value was 1.0888 and 1.0887. However GA-SA4 can found the best fitness chromosome faster than GA-SA1.

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A metaheuristic solution approach for the time-constrained project scheduling problem

Cited by 10 publications

References 42 publications

A common approximation framework for early work, late work, and resource leveling problems

A common approximation framework for early work, late work, and resource leveling problems

A decomposed branch-and-price procedure for integrating demand planning in personnel staffing problems

Hybrid Genetic Algorithms and Simulated Annealing for Multi-trip Vehicle Routing Problem with Time Windows

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