Verkauf durch Sack Fachmedien

El Amraoui / Layeb / Frikha

Advances in Operations Research Theory, Algorithms, and Applications

Proceedings of the Seventh International Conference of the Tunisian Operational Research Society (IC_TORS'25), Tunisia, April 11-13, 2025

Medium: Buch
ISBN: 978-3-032-27210-2
Verlag: Springer Nature Switzerland AG
Erscheinungstermin: 28.10.2026
vorbestellbar, Erscheinungstermin ca. November 2026

This book gathers a selection of peer-reviewed papers presented at the Seventh International Conference of the Tunisian Operations Research Society (IC_TORS'25) which was held in Sousse, Tunisia from 11th to 13th April 2025. It was sponsored by the Association of European Operational Research Societies (EURO), the International Federation of Operational Research Societies (IFORS), and INFORMS Bahrain International Group.

The book explores research issues in operational research and decision aid, highlighting recent theoretical advancements in areas such as linear, nonlinear, integer, stochastic, multilevel, and multi-objective optimization, as well as business analytics, simulation, decision theory, and multi-criteria decision aid. It also presents real-world applications across various sectors, including Industry 4.0, renewable energy, agriculture, green logistics and transportation, healthcare, water resource management, and sustainable, resilient supply chains.


Produkteigenschaften


  • Artikelnummer: 9783032272102
  • Medium: Buch
  • ISBN: 978-3-032-27210-2
  • Verlag: Springer Nature Switzerland AG
  • Erscheinungstermin: 28.10.2026
  • Sprache(n): Englisch
  • Auflage: Erscheinungsjahr 2026
  • Serie: Lecture Notes in Operations Research
  • Produktform: Kartoniert
  • Seiten: 636
  • Format (B x H): 155 x 235 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Herausgeber

Paper 01: Integrating Machine Learning and Multi-Criteria Decision-Making for Strategic Organizational Planning.- Paper 02: Random Forest-Guided Spherical Fuzzy AHP for Group-Decision Making Under Uncertainty.- Paper 03: Two-Stage Deep Reinforcement Learning Approach to Solving the Physician Scheduling Problem.- Paper 04: Machine Learning-Based Evapotranspiration Prediction and Irrigation Optimization in Tunisia.