LEADER 06099nam 22007455 450 001 9910726276403321 005 20230521201849.0 010 $a9789811980121$b(electronic bk.) 010 $z9789811980114 024 7 $a10.1007/978-981-19-8012-1 035 $a(MiAaPQ)EBC30547232 035 $a(Au-PeEL)EBL30547232 035 $a(OCoLC)1380465986 035 $a(DE-He213)978-981-19-8012-1 035 $a(BIP)085993304 035 $a(PPN)27061690X 035 $a(CKB)26736425200041 035 $a(EXLCZ)9926736425200041 100 $a20230521d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplications of Operational Research in Business and Industries $eProceedings of 54th Annual Conference of ORSI /$fedited by Angappa Gunasekaran, Jai Kishore Sharma, Samarjit Kar 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (512 pages) 225 1 $aLecture Notes in Operations Research,$x2731-0418 311 08$aPrint version: Gunasekaran, Angappa Applications of Operational Research in Business and Industries Singapore : Springer,c2023 9789811980114 327 $aChapter 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. . 330 $aEffective 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. 410 0$aLecture Notes in Operations Research,$x2731-0418 606 $aOperations research 606 $aMathematical optimization 606 $aBig data 606 $aMachine learning 606 $aArtificial intelligence?Data processing 606 $aOperations Research and Decision Theory 606 $aOptimization 606 $aBig Data 606 $aMachine Learning 606 $aData Science 610 $aTechnology 610 $aTechnology & Engineering 615 0$aOperations research. 615 0$aMathematical optimization. 615 0$aBig data. 615 0$aMachine learning. 615 0$aArtificial intelligence?Data processing. 615 14$aOperations Research and Decision Theory. 615 24$aOptimization. 615 24$aBig Data. 615 24$aMachine Learning. 615 24$aData Science. 676 $a658.4034 700 $aGunasekaran$b Angappa$01118646 701 $aSharma$b Jai Kishore$01359502 701 $aKar$b Samarjit$01359503 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910726276403321 996 $aApplications of Operational Research in Business and Industries$93373991 997 $aUNINA