A robust hybrid method for the multimode resource-constrained project scheduling problem

Szendrői, Etelka

doi:10.1556/pollack.5.2010.3.15

Cited by 9 publications

(4 citation statements)

References 4 publications

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“…Some of them suggest solving this problem as a task of constraints programming. In [7] the authors provide an overview of the main production scheduling approaches for operations management. These are approaches like Genetic Algorithm (GA), Ant Colony Optimization Algorithms (ACOA), Neural Networks (NN) and others.…”

Section: Some Earlier Resultsmentioning

confidence: 99%

Resource management simulation using multi-agent approach and semantic constraints

2017

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The resource management in a dynamic environment is a really complex problem. If semantic constraints are taken into account the complexity increases significantly. The problem definition of resource management using semantic constraints in the subject domain is demonstrated by means of an example of manufacturing scheduling. The application of multiagent approach is suggested and examined to solve the resource management problem. Experiments simulate two types of calculations of the resource allocation problem in manufacturing scheduling: the multi-agent approach and the sequential calculations. The experiments have demonstrated the effectiveness of multi-agent approach to solve the above defined problem.

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Section: Some Earlier Resultsmentioning

confidence: 99%

Resource management simulation using multi-agent approach and semantic constraints

2017

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“…In the current example the above sets have the following elements, see Fig. 1b: A={2, 3,4,5,6,7,8,9,10,11,20,22,24,26,28,30,32,34,35,close}; E={1,12,13,14,15,16,17,18,19,21,23,25,27,29,31,33,36,end}; V={ (1,2), (1,3), (1,4), (1,5), (1,6), (1,7), (1,8), (1,9), (1,10), (1,11), (2,12), (3,13), (4,14), (5,14), (6,15), (7,16), (8,17), (9,18), (10,18), (11,19) Other parameters of the mathematical programming model are the following: t i is the time from start-up to the i-th event occurs, as a result of the solution of the mathematical programming model; T i is the duration of the i-th activity as given in Table I; C i is the cost of the i-th activity as given in Table I; and C is the planned upper budget for the total project.…”

Section: Mathematical Programming Modelmentioning

confidence: 99%

“…Recent advances include the works Guerriero and Talarico [2] proposing a method to find the critical path in a deterministic activity-on-the-arc network with three different types of time constraints under consideration; while Li et al [3] introduced a two-stage minimum risk problem and developed a hybrid algorithm by combining a dynamic programming method with binary particle swarm optimization. SzendrĘi [4] developed a robust hybrid algorithm for the multi-mode resource-constrained project scheduling problem, where a harmony search algorithm was combined with a 'head-tail' local search procedure based on a Mixed Integer Linear Programming (MILP) formulation. Csébfalvi and Láng [5] presented an improved hybrid method for the resource-constrained project scheduling problem with discounted cash flows; their MILP formulation is relaxed with linear approximation.…”

Section: Introductionmentioning

confidence: 99%

Process network solution of a clothing manufacturer’s problem

Ercsey

2017

Pollack Periodica

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The current work focuses on a Hungarian clothing manufacturer's problem. First the industrial problem is presented; its corresponding critical pass method graph is depicted. To answer all emerging questions with respect to alternative possibilities, a large number of critical pass method problems have to be solved cumbersomely. Instead, first this graph is transformed into a process network. Alternatives specified by mainly financial necessities as well as human resource constraints can now be easily managed, namely where specific activities can be performed in different ways by various employee having different qualifications, requiring different durations and obviously respective costs can be considered within this model. These separate cases can commonly be handled within the resultant sole process network and the corresponding mathematical programming model.

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“…The result of a fuzzy scheduling method will be a robust fuzzy schedule that is immune to uncertainties in activity durations. Robust scheduling methods have also been considered by Szendrői [9] and Láng [6].…”

Section: Problem Formulationmentioning

confidence: 99%

A Hybrid Metaheuristic for Project Scheduling Problems with Fuzzy Activity Durations to support the Ös-Dráva Water Management Programme

Danka¹,

Csébfalvi²

Proceedings of the Eighth International Conference on Engineering Computational Technology

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Spatial developmental programs in Hungary are important to support economically lagging regions. As a result of their nature they can be considered as big projects, with long timescales, high levels of capital, causing significant impact on the targeted field. For an effective performance, an accurate planning phase is essentially important. In this paper we concentrate on the project scheduling element of planning, to reduce risk and gain knowledge on the possible, net present value and makespans. The Ős-Dráva program is a water-management based spatial development program. There have been no reference projects like this in Hungary that can support the scheduling of the problem with applicable information. This means that a highly uncertain case is considered with resource constraints implied. Our goal is to support the programme with an appropriate project scheduling method, resulting in a reliable makespan. For this we present a stochastic programming model and a hybrid metaheuristic for resource constrained project scheduling problems. The stochastic programming model was presented by Goel and Grossman[1], considering the net present value of subprojects. The hybrid metaheuristic was presented by Danka [2] which is a modification of the model developed by Csébfalvi [3]. In the presented approach, it is assumed that each activity duration is considered as a fuzzy variable which, can be described with an appropriate membership function. The heuristic algorithm produces "robust" resource-feasible schedules which are totally immune against uncertainties in the activity durations. The hybrid algorithm presented is based on the "Sounds of Silence" harmony search metaheuristic developed by Csébfalvi et al. [4, 5].

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A robust hybrid method for the multimode resource-constrained project scheduling problem

Cited by 9 publications

References 4 publications

Resource management simulation using multi-agent approach and semantic constraints

Resource management simulation using multi-agent approach and semantic constraints

Process network solution of a clothing manufacturer’s problem

A Hybrid Metaheuristic for Project Scheduling Problems with Fuzzy Activity Durations to support the Ös-Dráva Water Management Programme

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