Material Flow Optimization in Multi-Stage & Multi-Product Supply Chain: Theoretical and Practical Approach

Raju, Rajkanth

ISBN 10: 3330346906 / ISBN 13: 9783330346901

Editore: LAP LAMBERT Academic Publishing, 2017

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Dati bibliografici

• Titolo: Material Flow Optimization in Multi-Stage & Multi-Product Supply Chain: Theoretical and Practical Approach
• Editore: LAP LAMBERT Academic Publishing
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 3330346906
• ISBN 13: 9783330346901
• Rilegatura: Brossura
• Condizione: New

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Riassunto

Sustainable growth is the philosophy that most organizations look for to survive and compete in the global markets. The strategic importance of improving the quality of processes and services is nowadays a key factor to improve or at least to maintain their supply chain profitability, market share and competitiveness. With this boom in popularity of optimizing the supply chain drivers for maximizing the profits, this book aims to address one such driver, i.e, material flow optimization. The distribution and logistics cost comprise of about 30% of the total supply chain cost. In this book, integer-programming models to solve multi-echelon & multi-product supply chain are proposed to solve the distribution planning problems in the context of supply chain. The mixed integer programming model is formulated for four different scenarios of the supply chain distribution problem. A vehicle selection problem is also solved using a branch-and-bound technique (for shipment). Heuristic algorithms to solve the large-sized problems is proposed along with a real world case study. The heuristic methods solve the multi-stage transportation problem as aggregated single-stage transportation problem.

Informazioni sull?autore

Rajkanth Raju, PhD, M.S: Studied Business Management (Operations Management) at IIT Madras, India. Senior Data Scientist at Ford Motor Company based out in Chennai. Research interests are in the area of Manufacturing Data Analytics, Operations Management, Supply Chain Management, Vehicle Routing Problem, Inventory Optimization, and Scheduling.