Understanding the Complexities of Water, Sanitation & Hygiene Systems through Local Stakeholder Pers...

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منو

" Understanding the Complexities of Water, Sanitation & Hygiene Systems through Local Stakeholder Perspectives "
Valcourt, Nicholas Routhier Javernick-Will, Amy

Document Type	:	BL
Record Number	:	871558
Main Entry	:	Möllering, Karin
Title & Author	:	Inventory rationing : : a new modeling approach using Markov chain theory /\ Karin Möllering.
Publication Statement	:	Wiesbaden :: Springer Gabler,, [2019]
	:	, ©2007
Series Statement	:	Edition KWV
Page. NO	:	1 online resource
ISBN	:	3658242558
	:	: 9783658242558
	:	365824254X
	:	9783658242541
Contents	:	Intro; Contents; List of Tables; List of Figures; List of Abbreviations; List of Symbols; 1 Introduction; 1.1 Motivation; 1.2 Research Objectives; 1.3 Outline; Part I Foundations of Stochastic Inventory Control; 2 Basic Concepts of Inventory Management; 2.1 Inventory Management and Control; 2.2 Motivations for Holding Inventory; 2.3 Classification of Inventories; 2.3.1 The Strategic Perspective; 2.3.2 The Operational Perspective; 2.4 Inventory-related Costs; 2.4.1 Order Cost; 2.4.2 Holding Cost; 2.4.3 Penalty Cost; 2.5 Service Level; 3 Stochastic Inventory Control
	:	3.1 Characteristics of Inventory Models3.1.1 Management Decisions; 3.1.2 System-Inherent Characteristics; 3.2 Types of Inventory Control Policies; 3.3 Periodic Inventory Control; 3.3.1 Single-Period Inventory Control; 3.3.2 Multi-Period Inventory Control; 3.3.3 Service-Constraint Multi-Period Inventory Control; Part II Essential Stochastic Processes; 4 Markov Chains; 4.1 The Markov Property; 4.2 Homogeneous Markov Chains; 4.3 Limit Distribution and Invariant Distribution; 4.4 Communication Classes; 4.5 Class Properties; 4.5.1 Aperiodicity; 4.5.2 Recurrency and Transiency; 4.5.3 Class Criteria
	:	4.6 Uniqueness of Limit Distributions4.7 Multi-Dimensional Markov Chains; 4.8 Applications of Markov Chains; 5 Numerical Solution of Infinite Markov Chains; 5.1 System Reduction Approaches; 5.1.1 Reduced System Approaches; 5.1.2 Geometric Tail Distributions; 5.2 State Space Reduction Approaches; 5.2.1 Augmentations; 5.2.2 Pointwise Convergence; 5.3 Algorithms; 5.3.1 Sheskin's Partitioning Algorithm; 5.3.2 Power Iteration; 5.4 Criteria for Choosing a Specific Algorithm; 6 Comparing Stochastic Processes; 6.1 Stochastic Ordering for Distribution Functions; 6.2 The Sample Path Method