Soft Computing in Inventory Management (Inventory Optimization)

Description

This book presents a collection of mathematical models that deals with the real scenario in the industries. The primary objective of this book is to explore various effective methods for inventory control and management using soft computing techniques. Inventory control and management is a very tedious task faced by all the organizations in any sector of the economy. It makes decisions for policies, activities, and procedures in order to make sure that the right amount of each item is held in stock at any time. Many industries suffer from indiscipline while ordering and production mismatch. It is essential to provide best ordering policy to control such kind of mismatch in the industries. All the mathematical model solutions are provided with the help of various soft computing optimization techniques to determine optimal ordering policy.    This book is beneficial for practitioners, educators, and researchers. It is also helpful for retailers/managers for improving business functions and making more accurate and realistic decisions.  Contents Editors and Contributors Retailer’s Optimal Ordering Policy Under Supplier Credits When Demand is Fuzzy and Cloud Fuzzy 1 Introduction 2 Notations and Assumptions 2.1 Notations 2.2 Assumptions 3 Preliminary Concepts 3.1 Triangular Fuzzy Number (TFN) 3.2 2α- Cut of TFN 3.3 Cloud Triangular Fuzzy Number (CTFN) 3.4 Left and Right 2α- cut of CTFN 3.5 Yager’s Ranking Index Method (1981) 3.6 Yager’s Ranking Index Method for CTFN 4 Mathematical Modelling 4.1 Formulation of Fuzzy Mathematical Model 4.2 Formulation of Cloud Fuzzy Mathematical Model 5 Numerical Analysis and Proof of Convexity 6 Sensitivity Analysis 7 Conclusion and Future Scope References An Application of PSO to Study Joint Policies of an Inventory Model with Demand Sensitive to Trade Credit and Selling Price While Deterioration of Item Being Controlled Using Preventive Technique 1 Introduction 2 Notation and Assumptions 2.1 Notation 2.2 Assumptions 3 Mathematical Model 3.1 Retailer’s Total Profit Per Unit Time 3.2 Manufacturer Total Profit Per Unit Time 3.3 Joint Profit of Supply Chain 4 Solution Procedure 5 Numerical Examples 6 Sensitivity Analysis 7 Conclusion References Optimization of the Berth Allocation Problem to the Vessels Using Priority Queuing Systems 1 Introduction 2 Problem Description 3 Mathematical Model 3.1 Assumptions 4 Experimental Results and Discussion 5 Conclusions References Fuzzy Inventory Model for Deteriorating Items in a Supply Chain System with Time Dependent Demand Rate 1 Introduction 2 Assumptions and Notations 3 Mathematical Model 4 Numerical Example 5 Sensitivity Analysis 6 Conclusion References Credit Financing in a Two-Warehouse Inventory Model with Fuzzy Deterioration and Weibull Demand 1 Introduction 2 Literature Study 3 Prelimineries 4 Assumptions and Notation 4.1 Assumptions 4.2 Notation 5 Mathematical Model 5.1 Crisp Model 6 Fuzzy Model 6.1 Case 1: M leqtw leqT 6.2 Case 2: tw T 7 Numerical Examples 7.1 Crisp Model Versus Fuzzy Model 8 Sensitivity Analysis 9 Conclusion 10 Managerial Insights References Two-Warehouse Inventory of Sugar Industry Model for Deteriorating Items with Inflation Using Differential Evolution 1 Introduction 2 Related Works 3 Assumptions and Notations 4 Formulation and Solution of the Model 5 Evolutionary Algorithms 6 Numerical Illustration 7 Sensitivity Analysis 8 Conclusion References A Stackelberg Game Approach in Supply Chain for Imperfect Quality Items with Learning Effect in Fuzzy Environment 1 Introduction 2 Notations 2.1 Assumptions 2.2 Some Definitions 3 Mathematical Crisp Models 3.1 Buyer’s Model 3.2 Seller’s Model 3.3 The Non-cooperative Stackelberg Game Theory Approach 4 Mathematical Fuzzy Model 4.1 Buyer’s Fuzzy Model 4.2 Seller’s Fuzzy Model 4.3 Seller’s Stackelberg Fuzzy Model 4.4 The Buyer’s Stackelberg Fuzzy Model 5 Numerical Examples 6 Sensitivity Analysis 6.1 Effect of Learning on the Player’s Profit 6.2 Fuzzy Seller-Stackelberg 7 Observations 8 Conclusions References An Analytic and Genetic Algorithm Approach to Optimize Integrated Production-Inventory Model Under Time-Varying Demand 1 Introduction 2 Notations and Assumptions 2.1 Notations 2.2 Assumptions 3 Model Formulation 3.1 Manufacturer's Total Cost 3.2 Retailer's Total Cost 3.3 Joint Total Cost 4 Computational Algorithm 4.1 Analytical Approach 4.2 Genetic Algorithm Approach 5 Numerical Example and Sensitivity Analysis 5.1 Numerical Example 6 Conclusion References Sustainable Inventory Model with Carbon Emission Dependent Demand Under Different Carbon Emission Policies 1 Introduction 2 Assumptions and Notations 3 Mathematical Model 4 Solution Procedure 5 Numerical Examples 6 Sensitivity Analysis 7 Conclusion References Impact of Two Different Trade Credits Options on a Supply Chain with Joint and Independent Decision Under Trapezoidal Demand 1 Introduction 1.1 Notation 1.2 Assumptions 2 Mathematical Model 2.1 Supplier’s Model 2.2 Retailer’s Model 3 Joint and Independent Decision 3.1 Joint Decision 3.2 Independent Decision 4 Numerical Examples 5 Sensitivity Analysis 6 Conclusions References A Coordinated Single-Vendor Single-Buyer Inventory System with Deterioration and Freight Discounts 1 Introduction 2 Notations and Assumptions 2.1 Notations 2.2 Assumptions 3 Mathematical Model Formulation 4 Numerical Example and Sensitivity Analysis 4.1 Numerical Analysis 5 Sensitivity Analysis and Conclusion References