Reprint

Development and Optimization of Mathematical Models for Operations Research

Edited by
March 2023
260 pages
  • ISBN978-3-0365-6890-4 (Hardback)
  • ISBN978-3-0365-6891-1 (PDF)

This book is a reprint of the Special Issue Development and Optimization of Mathematical Models for Operations Research that was published in

Computer Science & Mathematics
Engineering
Physical Sciences
Public Health & Healthcare
Summary

The development of mathematical models and their optimization are fundamental for the effective resolution of many problems in operational research. In recent years, increased insights into real-world problems have led to the development of new mathematical models and optimization algorithms, contributing to the development of a research area with increasing practical relevance. This Special Issue is dedicated to works at the interface of mathematical modeling, optimization, and operations research, with a special focus on their real-world applications. The interest of the scientific community was significant, with submissions from authors from different countries from five continents, including Australia, China, Egypt, India, Israel, Portugal, Russia, Saudi Arabia, and the United States of America. Ten papers were accepted for publication after thorough peer review by dedicated reviewers with expertise in the relevant fields. We are confident that the papers selected for this Special Issue will attract a significant audience in the scientific community and will further stimulate research involving the development of mathematical models and their optimization.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
multi-time generalized Nash equilibrium problem; projected dynamical system; river basin pollution problem; traffic network equilibrium problem; variational inequality problem; freight transportation; heavy-haul railway; combination scheme; train timetable; genetic algorithm; trapezoidal type demand; interval-valued inventory costs; deterioration; preservation technology; QPSO algorithms; mixed integer nonlinear programming; piecewise linear approximation; branch and bound; pairwise comparison; matrix approximation; log-Chebyshev metric; tropical optimization; consumer preference; hotel selection; partial trade credit; cash discount; deteriorating items; EOQ; COVID-19; metaheuristics; project selection; portfolio management; resource; R&D; roadmap; program management; scheduling; unrelated parallel machines; sequence-dependent tasks; makespan; metaheuristics; genetic algorithm; statistical analysis; global optimization; unconstrained minimization; numerical approximations of gradients; meta-heuristics; stochastic parameters; conjugate gradient methods; efficient algorithm; performance profiles; comparisons; testing; discrete optimization; dragonfly algorithm; metaheuristics; optimization; swarm intelligence algorithms; traveling salesman problem