Application of uncertain variables to production planning in a class of manufacturing systems

Gasior, Dariusz; Józefczyk, Jerzy

doi:10.2478/v10175-010-0127-y

Cited by 4 publications

(6 citation statements)

References 14 publications

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“…Let P * UAC 1 ðvÞ be the optimal solution of the UP 1 depending on v [ D v and b T P * UAC 1 ðvÞ W Q * UAC 1 ðvÞ where: ; is a set of certainty thresholds for which a feasible solution exists. It was shown in Ga˛sior and Józefczyk (2009) that Q * UAC 1 ðvÞ is a non-increasing function of v, so if exists such a v [ D v for which Q * UAC 1 ð vÞ $ a and:…”

Section: Solution Algorithms For Uacmentioning

confidence: 98%

Admission control in computer networks with uncertain parameters

Gasior

2009

Kybernetes

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to deal with a problem of admission control in computer networks when some of their parameters are uncertain. The case is considered when the most common probabilistic description of the uncertainty cannot be used and another approach should be applied. Design/methodology/approach -The uncertain versions of admission control problem with quality of service requirements are considered. The uncertain variables are used to describe possible values of the unknown parameters in computer networks. Findings -Given are formulations for the admission control problem in computer networks with unknown values of the capacities based on the network utility maximization concept. Solution algorithms for all these problems are proposed. Research limitations/implications -It is assumed that an expert can describe possible values of uncertain network parameters in the form of a certainty distribution. Then the formalism of uncertain variables is applied and the knowledge of an expert is modelled with the use of certainty distributions. Decisions strongly depends on the quality of an expert's knowledge. Practical implications -Obtained admission control algorithms can be useful for planning and designing of computer networks. Originality/value -A new approach to the admission control problem in computer networks in the presence of uncertainty, in the case when the uncertain variable can be applied, is proposed and discussed.

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Section: Solution Algorithms For Uacmentioning

confidence: 98%

Admission control in computer networks with uncertain parameters

Gasior

2009

Kybernetes

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“…The link capacities C l and the QoS parameters x min r ; x max r are also subject to variations during the computer networks activities. It is assumed that these uncertainties are represented by the formalism of uncertain variables which is briefly presented (see Bubnicki, 2004;Gąsior and Józefczyk, 2009) for details). The uncertain variables approach can be treated as the special case of the fuzzy approach for numerical parameters in the case when their exact values are fixed and certain, but they are not known for the user.…”

Section: Uncertain Variablesmentioning

confidence: 99%

Utility-based models and decision making problems for selected network processes

Józefczyk

Gasior

2015

Kybernetes

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Purpose -The concept of utility was the first time applied in Economics. The purpose of this paper is to report its usefulness for the decision making in complex technological systems, in general and in computer networks, in particular. Three selected decision-making problems are considered, corresponding solution algorithms are explained and results of numerical experiments are presented for the selected real-world case study. Design/methodology/approach -Referring to similar decision-making problems in Economics, three problems of different time horizon are investigated: strategic investment planning, short-term network rate allocation and on-line network operating. Deterministic and uncertain versions are taken into account, and the latter one is handled more thoroughly. The formalism of uncertain variables is used to represent the parameter uncertainty which concerns users' demands for services in computer networks as well as network links' capacities. Corresponding optimization tasks are presented. Numerical experiments concerning a part of the computer network Pionier working in Poland confirmed the usefulness of the solution algorithms proposed. Findings -The carried out numerical experiments verified the importance and worth of the decisionmaking algorithms for the Pionier computer network. It particularly concerns the game theory-based algorithm solving the on-line network operating problem which enables calculating the rates for computer links distinctly, i.e., separately for every link. Research limitations/implications -More case studies should be considered to formulate more general corollaries. The application of utility concept for wireless sensor networks needs further studies on solution algorithms. Practical implications -The results can be directly applied to a class of modern computer networks, e.g., content delivery networks, self-managing networks, context aware networks, multilevel virtual networks. Originality/value -The paper presents the unified and systematic approach for individual results previously obtained, and it considers one case study.

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“…1, the set E R comprises 9 arcs: (1, 2), (1, 3), (3,5), (3,6), (4,5), (5, 9), (6, 5), (6, 7) and (7,9). Among them, unavoidable arcs are: (1, 2), (1,3), (3,6), (4,5), (5,9), (6,5) and (7,9). The arcs (3,5) and (6, 7) only may theoretically be deleted from the set E R if the resource allocation is modified.…”

Section: Robust Resource Allocationmentioning

confidence: 99%

“…An inherent feature of project execution is its uncertainty connected with the customers' changing requirements, erroneous estimation of task durations, temporary unavailability of resources (e.g., machinery failures) [1] etc. In order to compensate the effect of unpredictable production disruptions, robust scheduling is used.…”

Section: Introductionmentioning

confidence: 99%

Resource allocation for robust project scheduling

Klimek¹,

Łebkowski²

2011

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. The paper presents a formal description of the resource allocation problem for resource-constrained project scheduling. A schedule can be executed by various resource flow networks which may differ in terms of resistance to disruptions occurring during project execution. The authors define such criteria of evaluating a resource flow network which can be more useful than robustness metrics used so far in the research. The authors discuss the importance of robust scheduling for execution projects and propose metrics for resource allocation robustness which take into consideration the stability of the final schedule. Those metrics make it possible to carry out a more precise analysis concerning the properties of the resource flow network in terms of its robustness to disruptions in comparison with a well known flexibility indicator, flex.

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Application of uncertain variables to production planning in a class of manufacturing systems

Cited by 4 publications

References 14 publications

Admission control in computer networks with uncertain parameters

Admission control in computer networks with uncertain parameters

Utility-based models and decision making problems for selected network processes

Resource allocation for robust project scheduling

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