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|a (DE-627)JST05261042X
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|a (JST)2680705
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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|a Dacre, Marcus
|e verfasserin
|4 aut
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|a The Achievable Region Approach to the Optimal Control of Stochastic Systems
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|c 1999
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|a Text
|b txt
|2 rdacontent
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|a Computermedien
|b c
|2 rdamedia
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|a Online-Ressource
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|a The achievable region approach seeks solutions to stochastic optimization problems by characterizing the space of all possible performances (the achievable region) of the system of interest and optimizing the overall system-wide performance objective over this space. This is radically different from conventional formulations based on dynamic programming. The approach is explained with reference to a simple two-class queuing system. Powerful new methodologies due to the authors and co-workers are deployed to analyse a general multiclass queuing system with parallel servers and then to develop an approach to optimal load distribution across a network of interconnected stations. Finally, the approach is used for the first time to analyse a class of intensity control problems.
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|a Copyright 1999 The Royal Statistical Society
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|a Achievable Region
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|a Gittins Index
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|a Linear Programming
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|a Load Balancing
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|a Multiclass Queuing Systems
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|a Performance Space
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|a Stochastic Optimization
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|a Threshold Policy
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|a Business
|x Business economics
|x Commercial production
|x Production resources
|x Resource management
|x Time management
|x Scheduling
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|a Applied sciences
|x Engineering
|x Transportation
|x Traffic
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Decision theory
|x Operations research
|x Queuing theory
|x Queuing systems
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|a Applied sciences
|x Computer science
|x Computer engineering
|x Computer networking
|x Network servers
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Problem solving
|x Heuristics
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|a Applied sciences
|x Engineering
|x Control engineering
|x Control systems
|x Automatic control
|x Optimal control
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|a Business
|x Business administration
|x Corporate governance
|x Corporate policies
|x Cost control
|x Minimization of cost
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|a Mathematics
|x Pure mathematics
|x Geometry
|x Geometric properties
|x Convexity
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|a Applied sciences
|x Applied physics
|x Conservation laws
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|a Applied sciences
|x Computer science
|x Computer programming
|x Mathematical programming
|x Dynamic programming
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|a research-article
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1 |
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|a Glazebrook, Kevin
|e verfasserin
|4 aut
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1 |
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|a Nino-Mora, Jose
|e verfasserin
|4 aut
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0 |
8 |
|i Enthalten in
|t Journal of the Royal Statistical Society. Series B (Statistical Methodology)
|d Blackwell Publishers
|g 61(1999), 4, Seite 747-791
|w (DE-627)30219746X
|w (DE-600)1490719-7
|x 14679868
|7 nnns
|
773 |
1 |
8 |
|g volume:61
|g year:1999
|g number:4
|g pages:747-791
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|u https://www.jstor.org/stable/2680705
|3 Volltext
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|d 61
|j 1999
|e 4
|h 747-791
|