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Applications of operational research in business and industriesproceedings of 54th Annual Conference of ORSI /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applications of operational research in business and industriesedited by Angappa Gunasekaran, Jai Kishore Sharma, Samarjit Kar.
Reminder of title:	proceedings of 54th Annual Conference of ORSI /
other author:	Gunasekaran, A.
Corporate Body:	Operational Research Society of India.
Published:	Singapore :Springer Nature Singapore :2023.
Description:	1 online resource (xviii, 512 p.) :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Operations research
Online resource:	https://doi.org/10.1007/978-981-19-8012-1
ISBN:	9789811980121$q(electronic bk.)

Applications of operational research in business and industriesproceedings of 54th Annual Conference of ORSI /
Operational Research Society of India.Conference

Applications of operational research in business and industriesproceedings of 54th Annual Conference of ORSI /[electronic resource] :edited by Angappa Gunasekaran, Jai Kishore Sharma, Samarjit Kar. - Singapore :Springer Nature Singapore :2023. - 1 online resource (xviii, 512 p.) :ill., digital ;24 cm. - Lecture notes in operations research,2731-0418. - Lecture notes in operations research..

Chapter 1: Optimization of an inventory model with demand dependent on selling price and stock, nonlinear holding cost along with trade credit policy -- Chapter 2: Software Defect Prediction Through a Hybrid Approach Comprising of a Statistical Tool and a Machine Learning Model -- Chapter 3: Conservation of a prey species through optimal taxation: a model with Beddington-DeAngelis Functional Response -- Chapter 4: Investigate the reason for students' absenteeism in Engineering College in Fuzzy MCDM environment -- Chapter 5: Optimal inventory management policies for substitutable products considering non-instantaneous decay and cost of substitution.

Effective decision-making while trading off the constraints and conflicting multiple objectives under rapid technological developments, massive generation of data, and extreme volatility is of paramount importance to organizations to win over the time-based competition today. While agility is a crucial issue, the firms have been increasingly relying on evidence-based decision-making through intelligent decision support systems driven by computational intelligence and automation to achieve a competitive advantage. The decisions are no longer confined to a specific functional area. Instead, business organizations today find actionable insight for formulating future courses of action by integrating multiple objectives and perspectives. Therefore, multi-objective decision-making plays a critical role in businesses and industries. In this regard, the importance of Operations Research (OR) models and their applications enables the firms to derive optimum solutions subject to various constraints and/or objectives while considering multiple functional areas of the organizations together. Hence, researchers and practitioners have extensively applied OR models to solve various organizational issues related to manufacturing, service, supply chain and logistics management, human resource management, finance, and market analysis, among others. Further, OR models driven by AI have been enabled to provide intelligent decision-support frameworks for achieving sustainable development goals. The present issue provides a unique platform to showcase the contributions of the leading international experts on production systems and business from academia, industry, and government to discuss the issues in intelligent manufacturing, operations management, financial management, supply chain management, and Industry 4.0 in the Artificial Intelligence era. Some of the general (but not specific) scopes of this proceeding entail OR models such as Optimization and Control, Combinatorial Optimization, Queuing Theory, Resource Allocation Models, Linear and Nonlinear Programming Models, Multi-objective and multi-attribute Decision Models, Statistical Quality Control along with AI, Bayesian Data Analysis, Machine Learning and Econometrics and their applications vis-à-vis AI & Data-driven Production Management, Marketing and Retail Management, Financial Management, Human Resource Management, Operations Management, Smart Manufacturing & Industry 4.0, Supply Chain and Logistics Management, Digital Supply Network, Healthcare Administration, Inventory Management, consumer behavior, security analysis, and portfolio management and sustainability. The present issue shall be of interest to the faculty members, students, and scholars of various engineering and social science institutions and universities, along with the practitioners and policymakers of different industries and organizations.

ISBN: 9789811980121$q(electronic bk.)

Standard No.: 10.1007/978-981-19-8012-1doiSubjects--Topical Terms:

216699
Operations research

LC Class. No.: T57.6

Dewey Class. No.: 658.4034

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