Solving the discrete time/resource trade-off problem in project scheduling with genetic algorithms

Ranjbar, Mohammad; Kianfar, Farhad

doi:10.1016/j.amc.2007.02.109

Cited by 38 publications

(26 citation statements)

References 5 publications

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“…Most popular solution techniques for project scheduling problems include time-indexed and event-indexed MILP formulations, branch and bound schemes and metaheuristics, see, for example, Monma et al (1990), Demeulemeester et al (1996), Salewski et al (1997), Ranjbar et al (2007), Li and Womer (2012), Besikci et al (2013), and Ghoddousi et al (2013).…”

Section: Relation To Multi-mode Project Scheduling and Multiprocessormentioning

confidence: 99%

Minimizing the number of workers for one cycle of a paced production line

Dolgui¹,

Kovalev²,

Kovalyov³

et al. 2015

IFAC-PapersOnLine

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We consider a paced line that produces various products and consists of several assembly stations. Each product or semi-product requires a specific set of operations to be performed by identical workers. The assignment of operations to the stations and precedence relations between the operations are known. Operations assigned to different stations are performed simultaneously and those assigned to the same station are performed sequentially. No worker can perform more than one operation at a time. The processing time of an operation depends on the number of identical workers performing this operation. If a worker is assigned to an operation, he is busy with this task from its start till completion. The problem is to find a schedule, which specifies operation start times and assignment of workers to the operations, such that the line cycle time constraint and the number of workers box constraints for each operation are satisfied. We prove that the problem is NP-hard in the strong sense, suggest conventional and randomized heuristics, describe a reduction to a series of feasibility problems, show relation of the feasibility problem to multi-mode project scheduling and multiprocessor scheduling, and introduce a MILP model for the feasibility problem.

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Section: Relation To Multi-mode Project Scheduling and Multiprocessormentioning

confidence: 99%

Minimizing the number of workers for one cycle of a paced production line

Dolgui¹,

Kovalev²,

Kovalyov³

et al. 2015

IFAC-PapersOnLine

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“…Christodoulou et al (2009) proposed a method for resource allocation and scheduling of resource-constrained projects by use of a measure of the projects' entropy. Ranjbar and Kianfar (2007) used a genetic algorithm-based model to schedule each activity in one of its modes in order to minimize the project makespan.…”

Section: Introductionmentioning

confidence: 99%

“…He et al (2009) developed a model to assign activities' modes and progress payments so as to maximize the net present value of the contractor under the constraint of project deadline. Ranjbar and Kianfar (2007) used a genetic algorithm-based model to schedule each activity in one of its modes in order to minimize the project makespan.…”

Section: Introductionmentioning

confidence: 99%

Resource leveling scheduling by an ant colony-based model

Garmsiri

Abassi

2012

J Ind Eng Int

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In project scheduling, many problems can arise when resource fluctuations are beyond acceptable limits. To overcome this, mathematical techniques have been developed for leveling resources. However, these produce a hard and inflexible approach in scheduling projects. The authors propose a simple resource leveling approach that can be used in scheduling projects with multi-mode execution activities. In the mentioned approach, an ant algorithm determines the execution mode of each activity so that resource leveling index and project time become optimum. In the model, some visibility functions (defined in accordance with problem characteristics) are utilized, and the best, which return the best result, is selected for the model.

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“…Note that a combination of p j and r jk must be considered only if it is efficient, that is, (p j − 1) · r jk < ψ j and p j · (r jk − 1) < ψ j . This problem setting has been discussed by Demeulemeester et al [53] and Ranjbar and Kianfar [151]. Ranjbar et al [153] consider the case of multiple renewable resources.…”

Section: Tradeoff Problemsmentioning

confidence: 99%