Multi-objective, Integrated Supply Chain Design and Operation Under Uncertainty - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multi-objective, Integrated Supply Chain Design and Operation Under Uncertainty write by Christopher James Solo. This book was released on 2009. Multi-objective, Integrated Supply Chain Design and Operation Under Uncertainty available in PDF, EPUB and Kindle. This research involves the development of a flexible, multi-objective optimization tool for use by supply chain managers in the design and operation of manufacturing-distribution networks under uncertain demand conditions. The problem under consideration consists of determining the supply chain infrastructure; raw material purchases, shipments, and inventories; and finished product production quantities, inventories, and shipments needed to achieve maximum profit while fulfilling demand and minimizing supply chain response time. The development of the two-phase mathematical model parallels the supply chain planning process through the formulation of a strategic submodel for infrastructure design followed by a tactical submodel for operational planning. The deterministic strategic submodel, formulated as a multi-period, mixed integer linear programming model, considers an aggregate production planning problem in which long-term decisions such as plant construction, production capacities, and critical raw material supplier selections are optimized. These decisions are then used as inputs in the operational planning portion of the problem. The deterministic tactical submodel, formulated as a multi-period, mixed integer linear goal programming model, uses higher resolution demand and cost data, newly acquired transit time information, and the previously developed infrastructure to determine optimal non-critical raw material supplier selections; revised purchasing, production, inventory, and shipment quantities; and an optimal profit figure. The supply chain scenario is then modified to consider uncertain, long-term demand forecasts in the form of discrete economic scenarios. In this case, a multi-period, mixed integer robust optimization formulation of the strategic submodel is presented to account for the probabilistic demand data. Once the stochastic strategic submodel is presented, short-term, uncertain demand data is assumed to be available in the form of continuous probability distributions. By modifying decision makers' objectives regarding demand satisfaction, the distribution-based demand data is accounted for through the development of a multi-period, mixed integer chance-constrained goal programming formulation of the tactical submodel. In order to demonstrate the flexibility of both the deterministic and stochastic versions of the overall two-phase model, numerical examples are presented and solved. The resulting work provides supply chain managers with a flexible tool that can aid in the design and operation of real-world production-distribution networks, where uncertain demand data is available at different times and in various forms.
Supply Chain Optimization under Uncertainty
Supply Chain Optimization under Uncertainty - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Supply Chain Optimization under Uncertainty write by Barrie M. Cole. This book was released on 2014-12-15. Supply Chain Optimization under Uncertainty available in PDF, EPUB and Kindle. Drawing on cutting-edge research, this book proposes a new 'Supply Chain Optimization under Uncertainty’, technology. Its application can bring many proven benefits to supply chain entities, any associated service providers, and, of course, the customers. The technology can provide the best design and operating solution for a Supply Chain Network (SCN) that is subject to any prevailing conditions of Operational Uncertainty (OU). A SCN is defined as a network of production facilities, distribution centers and retail sales outlets. OU is defined as any relevant combination of i) multiple process objectives e.g. a business needs to maximize operating profits and to minimize inventory levels, ii) fuzziness (<, <=, >, or >=) e.g. sales <= 1500 t/mth and iii) probability e.g. sale of fertilizer is dependent on probabilistic rainfall. Following this method always enables the determination of realistic optimum supply chain solutions, since the effects of any operational uncertainties are always provided for. The book is arranged in two parts. The first part covers the theory and recent research into supply chain optimization under uncertainty. The second part documents the application of the newly proposed technology to an agricultural fertilizer’s (NPK, South Africa) supply chain.
Bi-Objective Integrated Supply Chain Network Design Under Supply and Demand Uncertainties
Bi-Objective Integrated Supply Chain Network Design Under Supply and Demand Uncertainties - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bi-Objective Integrated Supply Chain Network Design Under Supply and Demand Uncertainties write by Boyi Wu. This book was released on 2016. Bi-Objective Integrated Supply Chain Network Design Under Supply and Demand Uncertainties available in PDF, EPUB and Kindle. A supply chain has a network structure and its design involves production-distributiondecisions on the location of production, distribution facilities, capacities andtransportation quantities. A multi-echelon supply chain involving multiple suppliers andmultiple retailers for multiple products among multiple periods is considered in this thesis,which is required to be modeled as a multi-objective problem coping with uncertaintiesduring the process. The uncertainties considered in this thesis include demanduncertainties and suppliers disruptions. The end retailers demand is assumed to beuncertain following a certain distribution. Suppliers disruptions are represented by a setof discrete scenarios with given probabilities of occurrence of shrink in storage capacity,which can cause insufficient supplies from suppliers. Hence, the model in this thesis isdifferent from traditional supply chain network models under a deterministic case or themodels with uncertainties in demand only.In order to study the effects of the various uncertainties involved in the chain on theoptimal decisions, multiple methods are tested using a multi-objective mixed-integernonlinear model. After comparison of computational performance, the min-max methodis applied to obtain detailed mathematical solution. Numerical examples are conducted toillustrate the developed model with scenario analysis and sensitivity analysis is alsoconducted.
Optimization of Integrated Supply Chain Planning under Multiple Uncertainty
Optimization of Integrated Supply Chain Planning under Multiple Uncertainty - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimization of Integrated Supply Chain Planning under Multiple Uncertainty write by Juping Shao. This book was released on 2015-05-27. Optimization of Integrated Supply Chain Planning under Multiple Uncertainty available in PDF, EPUB and Kindle. The subject of this book is supply chain logistics planning optimization under multiple uncertainties, the key issue in supply chain management. Focusing on the strategic-alliance three-level supply chain, the model of supply chain logistics planning was established in terms of the market prices and the market requirements as random variables of manufactured goods with random expected value programming theory, and the hybrid intelligence algorithm solution model was designed. Aiming at the decentralized control supply chain, in which the nodes were unlimited expansion, the chance-constrained stochastic programming model was created in order to obtain optimal decision-making at a certain confidence level. In addition, the hybrid intelligence algorithm model was designed to solve the problem of supply chain logistics planning with the prices of the raw-materials supply market of the upstream enterprises and the prices of market demand for products of the downstream enterprises as random variables in the supply chain unit. Aimed at the three-stage mixed control supply chain, a logistics planning model was designed using fuzzy random programming theory with customer demand as fuzzy random variables and a hybrid intelligence algorithm solution was created. The research has significance both in theory and practice. Its theoretical significance is that the research can complement and perfect existing supply chain planning in terms of quantification. Its practical significance is that the results will guide companies in supply chain logistics planning in the uncertain environment.
Lean and Green Supply Chain Management
Lean and Green Supply Chain Management - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Lean and Green Supply Chain Management write by Turan Paksoy. This book was released on 2018-11-11. Lean and Green Supply Chain Management available in PDF, EPUB and Kindle. This book presents the latest developments in optimization and optimal control models; exact, approximate and hybrid methods; and their applications in lean and green supply chains. It examines supply chain network design and modeling, closed loop supply chains, and lean, green, resilient and agile or responsive networks, and also discusses corporate social responsibility and occupational health and safety. It particularly focuses on supply chain management under uncertainty – employing stochastic or nonlinear modeling, simulation based studies and optimization – multi-criteria decision-making and applications of fuzzy set theory, and covers various aspects of supply chain management such as risk management, supplier selection or the design of automated warehouses. Lastly, using experimental applications and practical case studies, it shows the impact of lean and green applications on vehicle/fleet management and operations management.
