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[null,"1.","Record Nr.",null,"UNINA9910823776003321"]
[null,null,"Autore",null,"Ganesh K."]
[null,null,"Titolo",null,"Resource allocation problems in supply chains / / by K. Ganesh, McKinsey & Company, Inc., Chennai, India [and three others]"]
[null,null,"Pubbl/distr/stampa",null,"Bingley : , : Emerald Insight, , 2015"]
[null,null,"ISBN",null,"1-78560-398-1"]
[null,null,"Edizione",null,"[First edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (197 p.)"]
[null,null,"Disciplina",null,"658.7"]
[null,null,"Soggetti",null,"Resource allocation - Mathematical models"]
[{"$nulls":4},"Mathematical optimization"]
[{"$nulls":4},"Programming (Mathematics)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"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"]
[{"$nulls":4},"1.3.3. Resource Allocation Variant in Multiple Measures Driven Capacitated Multi-Echelon Supply Chain Network1.3.4. Resource Allocation Variant in Integrated Decision and Upper Bound Driven Capacitated Multi-Echelon Supply Chain Network; 1.3.5. Resource Allocation Variant in Integrated Decision and Time Driven Capacitated Multi-Echelon Supply Chain Network; 1.3.6. Resource Allocation Variant in Integrated Decision, Bound and Time Driven Capacitated Multi-Echelon Supply Chain Network; 1.4. Scope of the Present Study; Section 2 Literature Review; 2.1. Resource Allocation Problem"]
[{"$nulls":4},"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 "]
[{"$nulls":4},"Capacity; 3.2. Solution Methodology to Solve BORAPVC"]
[{"$nulls":4},"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"]
[{"$nulls":4},"4.3.1. Performance of Solution Methodology4.4. Case Study Demonstration; 4.4.1. Problem Identification and Discussion; 4.4.1.1. Patient Distribution System (PDS); 4.4.1.2. Input to the Central Body; 4.4.1.3. Flow chart for the allocation of patients; 4.4.1.4. Problem identification; 4.4.1.5. Assumptions; 4.4.2. Formulation of the Problem; 4.4.3. Model Testing; 4.4.4. Analysis of Results and Discussion; 4.4.5. Managerial Implications; 4.4.6. Summary for Case Study; 4.5. Conclusion; Section 5 Multiple Measures Driven Capacitated Multi-Echelon Supply Chain Network"]
[{"$nulls":4},"5.1. Multiple Measures Resource Allocation Problem for Multi-Echelon Supply"]
[null,null,null,"Sommario/riassunto","Resource Allocation is the utilization of available resources in the system. This book focuses on development of models for 6 new, complex classes of RA problems in Supply Chain networks, focusing on bi-objectives, dynamic input data, and multiple performance measure based allocation and integrated allocation, and routing with complex constraints."]