LEADER 04930nam 2200577 450 001 9910797572503321 005 20230807221651.0 010 $a1-78560-398-1 035 $a(CKB)3710000000466178 035 $a(EBL)2190629 035 $a(MiAaPQ)EBC2190629 035 $a(Au-PeEL)EBL2190629 035 $a(CaPaEBR)ebr11092113 035 $a(CaONFJC)MIL824006 035 $a(OCoLC)919002289 035 $a(EXLCZ)993710000000466178 100 $a20150901d2015 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aResource allocation problems in supply chains /$fby K. Ganesh, McKinsey & Company, Inc., Chennai, India [and three others] 205 $aFirst edition. 210 1$aBingley :$cEmerald Insight,$d2015. 215 $a1 online resource (197 p.) 300 $aDescription based upon print version of record. 311 $a1-78560-399-X 320 $aIncludes bibliographical references and index. 327 $aFront 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 327 $a1.3.3. 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 327 $a2.2. 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 327 $a3.2.1. 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 327 $a4.3.1. 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 327 $a5.1. Multiple Measures Resource Allocation Problem for Multi-Echelon Supply 330 $aResource 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. 606 $aResource allocation$xMathematical models 606 $aMathematical optimization 606 $aProgramming (Mathematics) 615 0$aResource allocation$xMathematical models. 615 0$aMathematical optimization. 615 0$aProgramming (Mathematics) 676 $a658.7 700 $aGanesh$b K.$0880711 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910797572503321 996 $aResource allocation problems in supply chains$93796723 997 $aUNINA