Hierarchical Production Planning In A Multiple Plants And Multiple Distribution Centers Environment

Abstract.

Hierarchical and Supply Chain Planning describes the application of hierarchical planning techniques to all major functional areas of supply chain planning, including production, distribution, warehousing, transportation, inventory management, forecasting and performance management. The book reviews well-known, original hierarchical production planning techniques and implementations dating back several decades and numerous more current hierarchical planning methods and applications covering an array of supply chain activities. A number of novel hierarchical planning techniques and algorithms covering different components of supply chain planning are offered as is an original approach for integrating supply chain measurements into systems such as the balanced scorecard which evaluate total firm performance. The book covers the interests of private industry practitioners, academic researchers, and students of operations, logistics and supply chain management and planning.

This title describes the application of hierarchical planning techniques to all the major functional areas of supply chain planning, including production, distribution, warehousing, transportation, inventory management, forecasting and performance management. In particular, the book provides a comprehensive review and understanding of how hierarchical planning techniques and principles can contribute to the effective and efficient management and planning of supply chain activities. The book begins with a review of some well-known, original hierarchical production planning techniques and implementations dating back several decades. Building on this historical base, it then reviews numerous more current hierarchical planning methods and applications covering a wide array of supply chain activities. Additionally, the book offers a number of new and original hierarchical planning techniques and algorithms covering different components of supply chain planning.

Foundations of Computational Intelligence Volume 1: Learning and Approximation: Theoretical Foundations and Applications Learning methods and approximation algorithms are fundamental tools that deal with computationally hard problems and problems in which the input is gradually disclosed over time. Both kinds of problems have a large number of applications arising from a variety of fields, such as algorithmic game theory, approximation classes, coloring and partitioning, competitive analysis, computational finance, cuts and connectivity, inapproximability results, mechanism design, network design, packing and covering, paradigms for design and analysis of approxi- tion and online algorithms, randomization techniques, real-world applications, scheduling problems and so on. The past years have witnessed a large number of interesting applications using various techniques of Computational Intelligence such as rough sets, connectionist learning; fuzzy logic; evolutionary computing; artificial immune systems; swarm intelligence; reinforcement learning, intelligent multimedia processing etc. . In spite of numerous successful applications of C- putational Intelligence in business and industry, it is sometimes difficult to explain the performance of these techniques and algorithms from a theoretical perspective. Therefore, we encouraged authors to present original ideas dealing with the inc- poration of different mechanisms of Computational Intelligent dealing with Lea- ing and Approximation algorithms and underlying processes. This edited volume comprises 15 chapters, including an overview chapter, which provides an up-to-date and state-of-the art research on the application of Computational Intelligence for learning and approximation.

This book provides the fundamental underlying mathematical theory, numerical algorithms and effi cient computational tools for the solution of multi-level mixedinteger optimization problems. It can enable a vast array of decision makers and engineers (e.g. process engineers, bioengineers, chemical and civil engineers, and economists) to model, formulate and solve hierarchical decision making problems. The book gives detailed insights on multi-level optimization by comprehensive explanations, step-by-step numerical examples and case studies, plots, and diagrams.

The paper describes the development of a hierarchical planning and scheduling system for a multiple plant, multiple product, seasonal demand situation. In this hierarchical structure, optimal decisions at an aggregate level (planning) provide constraints for detailed decision making (scheduling). (Modified author abstract).

"This book presents relevant theoretical frameworks and most recent research findings in this area, providing significant theories for research students and scholars to carry out their continuous research as well as practitioners who aim to improve upon their understanding of distributed production planning"--

This book shows how graph theory and matrix approach, and fuzzy multiple attribute decision making methods can be used in manufacturing. It proposes a methodology that will make decision making in the manufacturing environment structured and systematic. The book uses case studies to present the applications of decision making methods in real manufacturing situations.

"Production planning is a crucial activity for companies to satisfy customers demand while minimizing cost. The objective of this research is to optimize the production planning and scheduling decisions of companies in petrochemical industry field. A Mixed-Integer Linear Programming (MILP) model is developed for the capacitated lot sizing and scheduling problem with sequence dependent setup costs; that considers the chain of multiple suppliers, affiliates, warehouses and customers. Different grades can be produced by each affiliate, and a changeover cost occurs when changing the production from one grade to another. The model integrates scheduling and lot-sizing decisions with the logistics functions of transportation and warehousing. In particular, it provides answers to questions regarding the amount of each raw material to be purchased from each supplier, sequence of production plans, inventory levels, and warehouse selection to satisfy orders. Petrochemical companies usually own several joint-ventures and centrally prepare the affiliates' production plans for the upcoming periods; their current planning procedures do not consider the overall costs in their supply-chain. The developed model will integrate their raw material costs, production and sequencing costs, inventory costs and transportation costs from the supplier side across the supply-chain to the customer side. The problem under study is considered an NP-Hard problem due to its complexity and size; therefore, a three stage heuristic was developed which provided good quality solutions with an acceptable computational time. The first stage of the heuristic works on reducing the complexity of the model by removing the sequencing decisions; where the resulting model decides only the size of lots for each affiliate. In the second and third stages, an iterative process is done to reduce the total setup and total holding costs while restoring the sequencing decisions. The heuristic was applied on different problem instances of different sizes and the reported results were within a range of 0.09% - 2.0% away from optimality. The development of the Mixed-Integer Linear Programming and the Three Stage Heuristic is the main contribution of this research."--Abstract.

The Seventh Edition of Production and Operations Analysis builds a solid foundation for beginning students of production and operations management. Continuing a long tradition of excellence, Nahmias and Olsen bring decades of combined experience to craft the most clear and up-to-date resource available. The authors’ thorough updates include incorporation of current technology that improves the effectiveness of production processes, additional qualitative sections, and new material on service operations management and servicization. Bolstered by copious examples and problems, each chapter stands alone, allowing instructors to tailor the material to their specific needs. The text is essential reading for learning how to better analyze and improve on all facets of operations.