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008			230521s2023 si | o |||| 0|eng d
020			_a9789811980121
024	7		_a10.1007/978-981-19-8012-1 _2doi
040			_aES-VaUEC _bspa _cES-VaUEC _dES-VaUE
050		4	_aT57.6 _b2023 EB
245	0	0	_aApplications of Operational Research in Business and Industries : _bProceedings of 54th Annual Conference of ORSI _cedited by Angappa Gunasekaran, Jai Kishore Sharma, Samarjit Kar
250			_a1st ed 2023
264		1	_aSingapore _c2023 _bSpringer International Publishing
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aLecture Notes in Operations Research _x2731-0418
505	0		_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. .
520			_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.
988			_aSpringer_Business_2023
650		7	_2embne _96736 _aAnálisis de sistemas _vCongresos y asambleas
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-8012-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE _n0
998			_b02/2024 _db _el _zSI