Reprint
Mathematical Methods for Operations Research Problems
Edited by
July 2024
326 pages
- ISBN978-3-7258-1626-2 (Hardback)
- ISBN978-3-7258-1625-5 (PDF)
https://doi.org/10.3390/books978-3-7258-1625-5 (registering)
Print copies available soon
This book is a reprint of the Special Issue Mathematical Methods for Operations Research Problems that was published in
Computer Science & Mathematics
Engineering
Physical Sciences
Public Health & Healthcare
Summary
This reprint of the Special Issue in the journal Mathematics presents research in the area of Operations Research. The subjects addressed in the 15 research papers cover a broad spectrum of subjects, such as machine learning, scheduling, timetabling, or graph theory.
Format
- Hardback
License and Copyright
© 2024 by the authors; CC BY-NC-ND license
Keywords
integer programming; digital geometry; non-traditional grids; shortest chamfer paths; 4D grid; linear programming; optimization; digital distances; chamfer distances; weighted distances; ant colony optimization; mathematical programming; negative learning; minimum dominating set; multi-dimensional knapsack problem; discrete optimization; operational research; computational geometry; complexity; algorithms; dynamic programming; clustering; k-center; p-center; sum-radii clustering; sum-diameter clustering; bi-objective optimization; Pareto Front; parallel programming; global total domination; total k-domination number; Best–Worst Method; Eigenvalue Method; Geometric Mean Method; Monte Carlo simulations; pairwise comparisons; sensitivity; scheduling; uniform machines; release time; delivery time; time complexity; algorithm; pressing process; printed circuit board; scheduling; mixed-integer linear programming; heuristic; swarm intelligence method; parameter control; adaptive technique; hidden Markov model; (s, Q)-policy; Markovian Arrival Process; N-policy; impatient customers; cryptocurrency; portfolio selection; return and risk measures; market capitalization; volume; attractiveness; PROMETHEE II; multicriteria model; carbon emission; carbon trading; e-commerce supply chain; sustainable development; clustering techniques; metaheuristics; machine learning; self-adaptive; parameter setting; exploration; exploitation; metaheuristics; machine learning; hybrid approach; optimisation; multiphase systems; heavy traffic; Little’s formula; timetabling problem; course university timetabling problem; AACSB standards; integer linear programming; n/a