Book ChapterDOI
Mixed Integer Programming Computation
Andrea Lodi
- pp 619-645
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TLDR
The first 50 years of Integer and Mixed-Integer Programming have taken us to a very stable paradigm for solving problems in a reliable and effective way, but a lot of work must still be done for improving the solvers and extending their modeling capability.Abstract:
The first 50 years of Integer and Mixed-Integer Programming have taken us to a very stable paradigm for solving problems in a reliable and effective way. We run over these 50 exciting years by showing some crucial milestones and we highlight the building blocks that are making nowadays solvers effective from both a performance and an application viewpoint. Finally, we show that a lot of work must still be done for improving the solvers and extending their modeling capability.read more
Citations
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Journal ArticleDOI
Tight and Compact MILP Formulation for the Thermal Unit Commitment Problem
TL;DR: In this article, a mixed-integer linear programming (MILP) reformulation of the thermal unit commitment (UC) problem is presented, which is simultaneously tight and compact.
Journal ArticleDOI
Bin Packing and Cutting Stock Problems: Mathematical Models and Exact Algorithms
TL;DR: The most important mathematical models and algorithms developed for the exact solution of the one-dimensional bin packing and cutting stock problems are reviewed and the performance of the main available software tools are evaluated.
Mixed Integer Linear Programming Formulation Techniques
TL;DR: This survey reviews advanced MIP formulation techniques that result in stronger and/or smaller formulations for a wide class of problems.
Journal ArticleDOI
Computation-Efficient Offloading and Trajectory Scheduling for Multi-UAV Assisted Mobile Edge Computing
TL;DR: A computation efficiency maximization problem is formulated in a multi-UAV assisted MEC system and an iterative optimization algorithm with double-loop structure is proposed to find the optimal solution.
Journal ArticleDOI
On learning and branching: a survey
Andrea Lodi,Giulia Zarpellon +1 more
TL;DR: This paper surveys learning techniques to deal with the two most crucial decisions in the branch-and-bound algorithm for Mixed-Integer Linear Programming, namely variable and node selections and describes the recent algorithms that instead explicitly incorporate machine learning paradigms.
References
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Journal ArticleDOI
Combinatorial optimization: algorithms and complexity
TL;DR: This clearly written, mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NPcomplete problems, more.
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Integer and Combinatorial Optimization
TL;DR: This chapter discusses the Scope of Integer and Combinatorial Optimization, as well as applications of Special-Purpose Algorithms and Matching.
Book ChapterDOI
An Automatic Method for Solving Discrete Programming Problems
Ailsa H. Land,Alison G. Doig +1 more
TL;DR: In the late 1950s there was a group of teachers and research assistants at the London School of Economics interested in linear programming and its extensions, in particular Helen Makower, George Morton, Ailsa Land and Alison Doig.
Book
Handbook Of Metaheuristics
Fred Glover,Gary A. Kochenberger +1 more
TL;DR: This book discusses Metaheuristic Class Libraries, Hyper-Heuristics, and Artificial Neural Networks for Combinatorial Optimization, which are concerned withMetaheuristic Algorithms and their applications in Search Technology.