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Resource allocation problems in supply chains /

"Resource Allocation (RA) involves the distribution and utilization of available resources in the system. Because resource availability is usually scarce and expensive, it becomes important to find optimal solutions to such problems. Thus RA problems represent an important class of problems fac...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Ganesh, K. (Autor), Malairajan, R. A. (Autor), Mohapatra, Sanjay (Autor), Punniymoorthy, M. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Bingley, UK : Emerald Group Publishing Limited, 2015.
Edición:First edition.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Ganesh, K.,  |e author. 
245 1 0 |a Resource allocation problems in supply chains /  |c by K. Ganesh, R.A. Malairajan, Sanja Mohapatra, M. Punniymoorthy. 
250 |a First edition. 
264 1 |a Bingley, UK :  |b Emerald Group Publishing Limited,  |c 2015. 
300 |a 1 online resource 
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588 0 |a Vendor-supplied metadata. 
504 |a Includes bibliographical references. 
520 |a "Resource Allocation (RA) involves the distribution and utilization of available resources in the system. Because resource availability is usually scarce and expensive, it becomes important to find optimal solutions to such problems. Thus RA problems represent an important class of problems faced by mathematical programmers. This book focuses on development of models and heuristics for six new and complex sub-classes of RA problems in Supply Chain (SC) networks, focusing on bi-objectives, dynamic input data, and multiple performance measures based allocation and integrated allocation, and routing with complex constraints. It considers six set of variants of the RA problems normally encountered in practice but have not yet been studied. These variants of the classical RA are complex and pertaining to both manufacturing and service industry."--Publisher 
505 0 |a Front Cover; Resource Allocation Problems in Supply Chains; Copyright page; Abstract; Contents; List of Tables; List of Figures; List of Symbols and Abbreviations; About the Authors; Section 1 Introduction; 1.1. Supply Chain Management; 1.2. Resource Allocation Problems in Supply Chain; 1.3. Motivation of Resource Allocation Problems; 1.3.1. Resource Allocation Variant in Bi-Objective Capacitated Supply Chain Network; 1.3.2. Resource Allocation Variant in Bi-Objective Bound Driven Capacitated Supply Chain Network 
505 8 |a 1.3.3. Resource Allocation Variant in Multiple Measures Driven Capacitated Multi-Echelon Supply Chain Network1.3.4. Resource Allocation Variant in Integrated Decision and Upper Bound Driven Capacitated Multi-Echelon Supply Chain Network; 1.3.5. Resource Allocation Variant in Integrated Decision and Time Driven Capacitated Multi-Echelon Supply Chain Network; 1.3.6. Resource Allocation Variant in Integrated Decision, Bound and Time Driven Capacitated Multi-Echelon Supply Chain Network; 1.4. Scope of the Present Study; Section 2 Literature Review; 2.1. Resource Allocation Problem 
505 8 |a 2.2. Review of the RA Variants Addressed in Current Research2.2.1. Bi-Objective Generalized Assignment Problem; 2.2.2. Multi-Commodity Network Flow Problem; 2.2.3. Multiple Measures Resource Allocation Problem; 2.2.4. Mixed Capacitated Arc Routing Problem; 2.2.5. Employee Routing Problem; 2.2.6. Vehicle Routing Problem with Backhauls with Time Windows; 2.3. Observations and Research Gap; 2.4. Summary; Section 3 Bi-Objective Capacitated Supply Chain Network; 3.1. Bi-Objective Resource Allocation Problem with Varying Capacity; 3.2. Solution Methodology to Solve BORAPVC 
505 8 |a 3.2.1. Mathematical Programming Model for BORAPVC3.2.2. Simulated Annealing with Population Size Initialization through Neighborhood Generation for GAP and BORAPVC; 3.2.2.1. Parameter settings for SAPING; 3.3. Computational Experiments and Results; 3.4. Conclusion; Section 4 Bi-Objective Bound Driven Capacitated Supply Chain Network; 4.1. Bi-Objective Resource Allocation Problem with Bound and Varying Capacity; 4.2. Solution Methodology to Solve IRARPUB; 4.2.1. Recursive Function Inherent Genetic Algorithm (REFING) for MCNF and BORAPBVC; 4.3. Computational Experiments and Results 
505 8 |a 4.3.1. Performance of Solution Methodology4.4. Case Study Demonstration; 4.4.1. Problem Identification and Discussion; 4.4.1.1. Patient Distribution System (PDS); 4.4.1.2. Input to the Central Body; 4.4.1.3. Flow chart for the allocation of patients; 4.4.1.4. Problem identification; 4.4.1.5. Assumptions; 4.4.2. Formulation of the Problem; 4.4.3. Model Testing; 4.4.4. Analysis of Results and Discussion; 4.4.5. Managerial Implications; 4.4.6. Summary for Case Study; 4.5. Conclusion; Section 5 Multiple Measures Driven Capacitated Multi-Echelon Supply Chain Network 
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650 0 |a Business logistics. 
650 0 |a Resource allocation. 
650 6 |a Logistique (Organisation) 
650 6 |a Affectation des ressources. 
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650 7 |a BUSINESS & ECONOMICS  |x Management.  |2 bisacsh 
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650 7 |a BUSINESS & ECONOMICS  |x Organizational Behavior.  |2 bisacsh 
650 7 |a Business logistics  |2 fast 
650 7 |a Resource allocation  |2 fast 
700 1 |a Malairajan, R. A.,  |e author. 
700 1 |a Mohapatra, Sanjay,  |e author. 
700 1 |a Punniymoorthy, M.,  |e author. 
758 |i has work:  |a Resource allocation problems in supply chains (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCGW4ydh9Kt9MvwCtDtQF83  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Erscheint auch als:  |n Druck-Ausgabe  |t Ganesh, K. Resource Allocation Problems in Supply Chains 
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