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Author: Wen Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 218
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Book Description
The dissertation contains two major research projects. In the first project, we first study a multi-period inventory planning problem. In each period, the firm under consideration can source from two possibly unreliable suppliers for a price-dependent demand. Our analysis suggests that the optimal procurement policy is neither a simple reorder-point policy nor a complex one without any structure, as previous studies suggest. Instead, we prove the existence of a reorder point for each supplier. No order is placed to that supplier for any inventory level above the reorder point and a positive order is issued to that supplier for almost every inventory level below the reorder point. We characterize conditions under which the optimal policy reveals monotone response to changes in the inventory level. Furthermore, two special cases of our model are examined in detail to demonstrate how our analysis generalizes a number of well-known results in the literature. In the second project, we study a long-run inventory planning problem in which the retailer can replenish inventory and change price adjustment. We establish that it is optimal to change the price from low to high in each replenishment cycle, the optimal order-up-to level may decrease when the ordering cost increases, and fewer customers are served when the unit cost of procurement increases. Additionally, we provide efficient algorithms to compute the optimal stocking and pricing policies.
Author: Wen Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 218
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Book Description
The dissertation contains two major research projects. In the first project, we first study a multi-period inventory planning problem. In each period, the firm under consideration can source from two possibly unreliable suppliers for a price-dependent demand. Our analysis suggests that the optimal procurement policy is neither a simple reorder-point policy nor a complex one without any structure, as previous studies suggest. Instead, we prove the existence of a reorder point for each supplier. No order is placed to that supplier for any inventory level above the reorder point and a positive order is issued to that supplier for almost every inventory level below the reorder point. We characterize conditions under which the optimal policy reveals monotone response to changes in the inventory level. Furthermore, two special cases of our model are examined in detail to demonstrate how our analysis generalizes a number of well-known results in the literature. In the second project, we study a long-run inventory planning problem in which the retailer can replenish inventory and change price adjustment. We establish that it is optimal to change the price from low to high in each replenishment cycle, the optimal order-up-to level may decrease when the ordering cost increases, and fewer customers are served when the unit cost of procurement increases. Additionally, we provide efficient algorithms to compute the optimal stocking and pricing policies.
Author: Nita H. Shah
Publisher: Springer Nature
ISBN: 9811396981
Category : Business & Economics
Languages : en
Pages : 470
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Book Description
This book discusses inventory models for determining optimal ordering policies using various optimization techniques, genetic algorithms, and data mining concepts. It also provides sensitivity analyses for the models’ robustness. It presents a collection of mathematical models that deal with real industry scenarios. All mathematical model solutions are provided with the help of various optimization techniques to determine optimal ordering policy. The book offers a range of perspectives on the implementation of optimization techniques, inflation, trade credit financing, fuzzy systems, human error, learning in production, inspection, green supply chains, closed supply chains, reworks, game theory approaches, genetic algorithms, and data mining, as well as research on big data applications for inventory management and control. Starting from deterministic inventory models, the book moves towards advanced inventory models. The content is divided into eight major sections: inventory control and management – inventory models with trade credit financing for imperfect quality items; environmental impact on ordering policies; impact of learning on the supply chain models; EOQ models considering warehousing; optimal ordering policies with data mining and PSO techniques; supply chain models in fuzzy environments; optimal production models for multi-items and multi-retailers; and a marketing model to understand buying behaviour. Given its scope, the book offers a valuable resource for practitioners, instructors, students and researchers alike. It also offers essential insights to help retailers/managers improve business functions and make more accurate and realistic decisions.
Author: Stefan Seuring
Publisher: Springer Science & Business Media
ISBN: 9783790815009
Category : Business & Economics
Languages : en
Pages : 452
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Book Description
Supply Chain Management and Cost Management are important developments helping companies to respond to increased global competition and demanding customer needs. Within the 23 chapters of the book, more than 35 authors provide insights into new concepts for cost control in supply chains. The frameworks presented are illustrated with case studies from the automotive, textile, white goods, and transportation industry as well as from retailing. Academics will benefit from the wide range of approaches presented, while practitioners will learn from the examples how their own company and the supply chains which they compete in, can be brought to lower costs and better performance.
Author: Changyuan Yan
Publisher:
ISBN:
Category : Business logistics
Languages : en
Pages : 288
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Book Description
This thesis investigates the optimal decisions for maximizing the expected profit level of a supply chain when market demand is price-sensitive. We examine two-echelon supply chains consisting of a single manufacturer and one or more retailers, where the organizations simultaneously determine the retail price, production lot size and inventory replenishment schedules to maximize the profit of the entire supply chain. In particular, we first develop a model for singlemanufacturer single-retailer (SMSR) supply chains, assuming deterministic market demand. We then extend the SMSR model to supply chains with multiple-retailers (i.e. SMMR supply chains). Finally, we examine both SMSR and SMMR supply chains in stochastic market demand environments. We show that supply chain cooperation/centralization brings higher profits for the manufacturer and the retailer(s), and benefits retail consumers with a lower retail price. We propose efficient algorithms for our models and illustrate them through numerical examples. Managerial implications and future research directions are also discussed.
Author: Lisha Duan
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Given the popularity of inventory models with supplier selection, this research aims to develop mathematical models for the integrated procurement, inventory planning, and pricing problems in the presence of multiple capacitated suppliers and price-sensitive demand in supply chains, simultaneously determining the selling pricing and inventory policy under a variety of supply contracts. We starts with the development of an operational planning model in a demand-driven serial supply chain with multiple capacitated suppliers. Taking into account delivery time and order frequency, the suppliers offer a novel price break scheme, which is beneficial to both the supplier and the buyer. A mixed-integer linear programming (MILP) formulation is developed to address this dynamic supplier selection and inventory management model aiming at minimizing the overall incurred cost across the entire supply chain with capacity constraints in production, inventory, and transportation. Then, the length of the time period is considered as a variable. A new MILP formulation is derived when each period of the model is split into multiple sub-periods, and under certain conditions, it is proved that the optimal solution and objective value of the original model form a feasible solution and an upper bound for the derived model. Sufficient evidence demonstrates that the length of the time period has a significant influence on supplier selection, lot sizing allocation, and inventory planning decisions. Then, we investigate joint decision making of supplier selection, pricing, and inventory lot-sizing in a two-stage supply chain, where suppliers feature certain capacity and quality levels and the retailer faces a price-sensitive demand, characterized by the logit function. Multiple orders can be placed to potential suppliers within a repeating order cycle. The retailer purchases the items satisfying a lower bound on the average quality level to meet customer demand. In this context, we develop a mathematical model to find an optimal solution for the selling price and inventory replenishment policy, including the set of selected suppliers, order frequency, and order quantity. We further derive a lower bound on the optimal retail price and based on a two-stage piecewise linear approximation (PLA) technique, we develop heuristic algorithms to yield near-optimal solutions to the proposed model. Besides, we provide sufficient justification for the selection of the logit demand function as well as a comparison with other demand functions. A numerical study further suggests the importance of using a precise demand curve to select the set of suppliers, coordinate inventory, and accurately optimize the profit function. Next, we extend the joint pricing, supplier selection and inventory replenishment model to a serial supply chain with multiple stages in a centralized control scenario. Within this supply chain, the first stage faces a supplier selection decision for a particular product that experiences a price-sensitive demand. The buying stage needs to decide which suppliers to choose and how to allocate orders, determining the optimal inventory policy for all stages and the retail price to offer to end customers, while maximizing the total profit of the supply chain. The problem is formulated as a mixed integer nonlinear programming (MINLP) model and a heuristic algorithm is proposed to overcome the complexity of the model. Then, we analyze a special case that considers only one uncapacitated supplier and one buyer. An efficient heuristic is developed and computational experiments are carried out to examine the performance of the proposed heuristics. In addition, we provide a series of numerical examples to illustrate our results and analyze the impact of the parameters within a sensitivity analysis. Finally, we study a pricing and purchasing problem in a two-stage supply chain with one supplier and one retailer, where the retailer faces the price-sensitive demand and the supplier coordinates the supply chain with controllable delivery deviation. Both the retailers demand and the suppliers lead time are stochastic. A risk sharing supply contract is adopted and the supplier compensates the retailer by paying a portion of penalties for early/late delivery. In this direction, we establish a model with a game-theoretic approach to achieve supply chain coordination, simultaneously determining the retailers selling price, order quantity, and order date as well as the suppliers lead time variance. Besides, the models with respect to the constant delivery deviation are also developed and analyzed. Finally, a numerical example is presented and sensitivity analysis regarding the pricing and penalty parameters provide in-depth managerial insights for decision makers.
Author: Dinesh K. Sharma
Publisher: Springer Nature
ISBN: 9811963371
Category : Business & Economics
Languages : en
Pages : 293
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Book Description
This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included.The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics.
Author: Joseph Geunes
Publisher: Springer Science & Business Media
ISBN: 0387262814
Category : Business & Economics
Languages : en
Pages : 418
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Book Description
Supply Chain Optimization captures the latest results in a segment of current research activity in supply chain management. This research area focuses on applying optimization techniques to supply chain management problems. The research papers that make up the volume provide a snapshot of state-of-the-art optimization methods within the field. This book presents rigorous modelling approaches for supply chain operations problems with a goal of improving supply chain performance (or the performance of some segment thereof). It contains high-quality works from leading researchers in the field whose expertise fits within this scope. The book provides a diverse blend of research topics and novel modelling and solution approaches for difficult classes of supply chain operations, planning, and design problems.
Author: Nita H. Shah
Publisher: Springer Nature
ISBN: 9811617295
Category : Business & Economics
Languages : en
Pages : 237
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Book Description
This book provides several inventory models for making the right decision in inventory management under different environments. Basically, the optimal ordering policies are determined for situations with and without shortages in production-inventory systems. The chapters in the book include various features of inventory modeling i.e., inflation, deterioration, supply chain, learning, credit financing, carbon emission policy, stock-dependent demand, among others. The book is a useful resource for academicians, researchers, students, practitioners, and managers who can be benefited with the policies provided in the chapters of the book.
Author: Narendra Agrawal
Publisher: Springer Science & Business Media
ISBN: 0387789030
Category : Business & Economics
Languages : en
Pages : 335
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Book Description
In today's retail environment, characterized by product proliferation, price competition, expectations of service quality, and advances in technology, many organizations are struggling to maintain profitability. Rigorous analytical methods have emerged as the most promising solution to many of these complex problems. Indeed, the retail industry has emerged as a fascinating choice for researchers in the field of supply chain management. In Retail Supply Chain Management, leading researchers provide a detailed review of cutting-edge methodologies that address the complex array of these problems. A critical resource for researchers and practitioners in the field of retailing, chapters in this book focus on three key areas: (1) empirical studies of retail supply chain practices, (2) assortment and inventory planning, and (3) integrating price optimization into retail supply chain decisions.
Author: Robert A. Davis
Publisher: John Wiley & Sons
ISBN: 1119174023
Category : Business & Economics
Languages : en
Pages : 320
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Book Description
Remove built-in supply chain weak points to more effectively balance supply and demand Demand-Driven Inventory Optimization and Replenishment shows how companies can support supply chain metrics and business initiatives by removing the weak points built into their inventory systems. Beginning with a thorough examination of Just in Time, Efficient Consumer Response, and Collaborative Forecasting, Planning, and Replenishment, this book walks you through the mathematical shortcuts set up in your management system that prevent you from attaining supply chain excellence. This expanded second edition includes new coverage of inventory performance, business verticals, business initiatives, and metrics, alongside case studies that illustrate how optimized inventory and replenishment delivers results across retail, high-tech, men's clothing, and food sectors. Inventory optimization allows you to avoid out-of-stock situations without impacting the bottom line with excessive inventory maintenance. By keeping just the right amount of inventory on hand, your company is better able to meet demand without sacrificing the cost-effectiveness of other supply chain strategies. The trick, however, is determining "just the right amount"—and this book provides the background and practical guidance you need to do just that. Examine the major supply chain strategies of the last 30 years Remove the shortcuts that prohibit supply chain excellence Optimize your supply/demand balance in any vertical Overcome systemic weaknesses to strengthen the bottom line Inventory optimization is benefitting companies around the world, as exemplified here by case studies involving Matas, PWT, Wistron, and Amway. When inefficiencies are built into the system, it's only smart business to identify and remove them—and implement a new streamlined process that runs like a well-oiled machine. Demand-Driven Inventory Optimization and Replenishment is an essential resource for exceptional supply chain management.
