Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

A fuzzy periodic review integrated inventory model involving stochastic demand, imperfect production process and inspection errors

In this study, we investigate an integrated production-inventory system consisting of a single-vendor and single-buyer. The buyer manages its inventory level periodically at a certain period of time. We consider a fuzzy annual demand, imperfect production, inspection errors, partial backordering, and adjustable production rate in the proposed model. Additionally, it is assumed that the protection interval demand follows a normal distribution. The model contributes to the current literature by allowing the inclusion of fuzzy annual demand, adjustable production rate and imperfect production and inspection processes. Our objective is to optimize the number of deliveries from vendor to buyer, the buyer’s review period, and the vendor’s production rate, so that the joint expected total annual cost incurred has the minimum value. Furthermore, an iterative procedure is proposed to find the optimal solutions of the model. We also provide a numerical example and conduct a simple sensitivity analysis to illustrate the model’s behaviour and feasibility. The results from the sensitivity analysis show that the defective rate, type I inspection error, fuzzy annual demand, fixed production cost, variable production cost and setup cost give impacts to both the review period and production rate. Finally, it is concluded that the proposed model can be applied by managers or practitiones for managing inventories across the supply chain involving a vendor and a buyer

SINGLE PERIOD INVENTORY MODEL WITH STOCHASTIC DEMAND AND PARTIAL BACKLOGGING

ABSTRACT In this present scenario of world economy both the factors like salvage and stock-out situations are equally important. Continuous sources of uncertainty (stochastic demand), has a different impact on optimal inventory settings and prevents optimal solutions from being found in closed form. In this paper an approximate closed-form solution is developed using a single stochastic period of demand. Assorted level of demand is viewed in form of a special class of inventory evolution known as finite inventory process. Here the Inventory process is reviewed in form of three cases. This paper involves the study of optimality of the expected cost using the SCBZ property. Shortage cost is kept in view, in order to meet the customer demand. Finally this paper aims to show the optimal solution for three cases of finite inventory model in which the demand is varied according to the SCBZ property. Appropriate Numerical illustrations provide a justification for its unique existence

SINGLE PERIOD INVENTORY MODEL WITH STOCHASTIC DEMAND AND PARTIAL BACKLOGGING

ABSTRACT In this present scenario of world economy both the factors like salvage and stock-out situations are equally important. Continuous sources of uncertainty (stochastic demand), has a different impact on optimal inventory settings and prevents optimal solutions from being found in closed form. In this paper an approximate closed-form solution is developed using a single stochastic period of demand. Assorted level of demand is viewed in form of a special class of inventory evolution known as finite inventory process. Here the Inventory process is reviewed in form of three cases. This paper involves the study of optimality of the expected cost using the SCBZ property. Shortage cost is kept in view, in order to meet the customer demand. Finally this paper aims to show the optimal solution for three cases of finite inventory model in which the demand is varied according to the SCBZ property. Appropriate Numerical illustrations provide a justification for its unique existence

Value of supplier's capacity information in a two-echelon supply chain

Cataloged from PDF version of article.In traditional supply chain models it is generally assumed that full information is available to all parties involved. Although this seems reasonable, there are cases where chain members are independent agents and possess different levels of information. In this study, we analyze a two-echelon, single supplier-multiple retailers supply chain in a single-period setting where the capacity of the supplier is limited. Embedding the lack of information about the capacity of the supplier in the model, we aim to analyze the reaction of the retailers, compare it with the full-information case, and assess the value of information and the effects of information asymmetry using game theoretic analysis. In our numerical studies, we conclude that the value of information is highly dependent on the capacity conditions and estimates of the retailers, and having information is not necessarily beneficial to the retailers

Value of supplier's capacity information in a two-echelon supply chain

In traditional supply chain models it is generally assumed that full information is available to all parties involved. Although this seems reasonable, there are cases where chain members are independent agents and possess different levels of information. In this study, we analyze a two-echelon, single supplier-multiple retailers supply chain in a single-period setting where the capacity of the supplier is limited. Embedding the lack of information about the capacity of the supplier in the model, we aim to analyze the reaction of the retailers, compare it with the full-information case, and assess the value of information and the effects of information asymmetry using game theoretic analysis. In our numerical studies, we conclude that the value of information is highly dependent on the capacity conditions and estimates of the retailers, and having information is not necessarily beneficial to the retailers

Optimal policy for multi-item systems with stochastic demands, backlogged shortages and limited storage capacity

Producción CientíficaIn this paper, an inventory model for multiple products with stochastic demands is developed. The scheduling period or inventory cycle is known and prescribed. Demands are independent random variables and they follow power patterns throughout the inventory cycle. For each product, an aggregate cycle demand is realized first and then the demand is released to the inventory system gradually according to power patterns within a cycle. These demand patterns express different ways of drawing units from inventory and can be a good approach to modelling customer demands in inventory systems. Shortages are allowed and they are fully backlogged. It is assumed that the warehouse where the items are stored has a limited capacity. For this inventory system, we determine the inventory policy that maximizes the expected profit per unit time. An efficient algorithmic approach is proposed to calculate the optimal inventory levels at the beginning of the inventory cycle and to obtain the maximum expected profit per unit time. This inventory model is applicable to on-line sales of a wide variety of products. In this type of sales, customers do not receive the products at the time of purchase, but sellers deliver goods a few days later. Also, this model can be used to represent inventories of products for in-shop sales when the withdrawal of items from the inventory is not at the purchasing time, but occurs in a period after the sale of the products. This inventory model extends various inventory systems studied by other authors. Numerical examples are introduced to illustrate the theoretical results presented in this work.Ministerio de Ciencia, Innovación y Universidades - Fondo Europeo de Desarrollo Regional (project MTM2017-84150-P

Supply chain coordination and integration under yield loss

The primary objective of this dissertation is to develop analytical models for typical supply chain situations to help supply chain decision-makers under supply yield loss. We derive solution procedures for each model and present several managerial insights obtained from our models through numerical examples. Additionally, this research provides decision-makers insights on how to incorporate uncertainty in demand and supply and shortage information into a mathematical model. This study deals with three forms of integrated cost-profit models under different scenarios including coordination policy and supply yield loss in a two-stage supply chain involving a retailer and a supplier, dealing with a single product under deterministic condition. We compare the profits of the whole supply chain system under the coordinated policy with those of individual decision making approaches and demonstrate the efficiency of coordination. These models attempts to find the optimal solutions for the retailer’s order quantity, quality level, amount of emergency procurement, and the production and shipment decisions of the supplier, so that the resulting joint total profit for the entire supply chain is maximized. We illustrate our model and the potential benefits of outsourcing in a supply chain system through a numerical example. Extending the analyses obtained above, we then develop models for an integrated supplier–retailer supply chain under imperfect production and shortages, with the additional decision variable of market pricing on the part of the retailer. We assume that market demand is sensitive to the retailer’s selling price and study the combined operation and pricing decisions in the supply chain. We develop profit maximization models for the cases of independent and joint optimization. The results of obtained from our analyses demonstrate that the individual profit, as well as joint profit can be increased by our suggested model, under a non-linear price dependent demand function. In addition, the results with retailer-supplier coordination tend to be superior, which leads to illustrate that setting appropriately retailer’s selling price can increase market demand and the profits of both parties, as well as that of the supply chain. Finally, numerical examples are presented to illustrate these models, and the sensitivity analyses of a selected set of model parameters on the total profit is conducted. A major finding of this study is that coordination between the retailer and the supplier improves channel profit significantly. Furthermore, the possibility of external procurement tends to improve total system profitability as the price sensitivity of demand increases.Ph.D., Business Administration -- Drexel University, 201

Classification of the Existing Knowledge Base of OR/MS Research and Practice (1990-2019) using a Proposed Classification Scheme

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordOperations Research/Management Science (OR/MS) has traditionally been defined as the discipline that applies advanced analytical methods to help make better and more informed decisions. The purpose of this paper is to present an analysis of the existing knowledge base of OR/MS research and practice using a proposed keywords-based approach. A conceptual structure is necessary in order to place in context the findings of our keyword analysis. Towards this we first present a classification scheme that relies on keywords that appeared in articles published in important OR/MS journals from 1990-2019 (over 82,000 articles). Our classification scheme applies a methodological approach towards keyword selection and its systematic classification, wherein approximately 1300 most frequently used keywords (in terms of cumulative percentage, these keywords and their derivations account for more than 45% of the approx. 290,000 keyword occurrences used by the authors to represent the content of their articles) were selected and organised in a classification scheme with seven top-level categories and multiple levels of sub-categories. The scheme identified the most commonly used keywords relating to OR/MS problems, modeling techniques and applications. Next, we use this proposed scheme to present an analysis of the last 30 years, in three distinct time periods, to show the changes in OR/MS literature. The contribution of the paper is thus twofold, (a) the development of a proposed discipline-based classification of keywords (like the ACM Computer Classification System and the AMS Mathematics Subject Classification), and (b) an analysis of OR/MS research and practice using the proposed classification