EURO Advanced Tutorials in Operational Research

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EURO Advanced Tutorials in Operational Research
Edited by M. Grazia Speranza and José Fernando Oliveira
Discipline Operational Research
Publisher Springer Science+Business Media on behalf of the Association of European Operational Research Societies
Published= 2014-present
Website http://www.springer.com/series/13840

The EURO Advanced Tutorials in Operational Research are a series of short books devoted to advanced topics in Operational Research that are not available in textbooks. The scope of a Tutorial is to provide more detail about advanced topics in a relevant field to researchers and practitioners. The Book Series was established in 2014 and is published by Springer Science+Business Media. It is an official publication of the Association of European Operational Research Societies.

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Related Research Articles

Quadratic programming (QP) is the process of solving certain mathematical optimization problems involving quadratic functions. Specifically, one seeks to optimize a multivariate quadratic function subject to linear constraints on the variables. Quadratic programming is a type of nonlinear programming.

<span class="mw-page-title-main">Linear programming</span> Method to solve optimization problems

Linear programming (LP), also called linear optimization, is a method to achieve the best outcome in a mathematical model whose requirements and objective are represented by linear relationships. Linear programming is a special case of mathematical programming.

<span class="mw-page-title-main">Mathematical optimization</span> Study of mathematical algorithms for optimization problems

Mathematical optimization or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries.

In computational intelligence (CI), an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the quality of the solutions. Evolution of the population then takes place after the repeated application of the above operators.

An integer programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers. In many settings the term refers to integer linear programming (ILP), in which the objective function and the constraints are linear.

<span class="mw-page-title-main">Combinatorial optimization</span> Subfield of mathematical optimization

Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, where the set of feasible solutions is discrete or can be reduced to a discrete set. Typical combinatorial optimization problems are the travelling salesman problem ("TSP"), the minimum spanning tree problem ("MST"), and the knapsack problem. In many such problems, such as the ones previously mentioned, exhaustive search is not tractable, and so specialized algorithms that quickly rule out large parts of the search space or approximation algorithms must be resorted to instead.

In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, tune, or select a heuristic that may provide a sufficiently good solution to an optimization problem or a machine learning problem, especially with incomplete or imperfect information or limited computation capacity. Metaheuristics sample a subset of solutions which is otherwise too large to be completely enumerated or otherwise explored. Metaheuristics may make relatively few assumptions about the optimization problem being solved and so may be usable for a variety of problems.

ECLiPSe is a software system for the development and deployment of constraint logic programming applications, e.g., in the areas of optimization, planning, scheduling, resource allocation, timetabling, transport, etc. It is also suited for teaching most aspects of combinatorial problem solving, e.g., problem modeling, constraint programming, mathematical programming, and search techniques. It contains constraint solver libraries, a high-level modeling and control language, interfaces to third-party solvers, an integrated development environment and interfaces for embedding into host environments.

Placement is an essential step in electronic design automation — the portion of the physical design flow that assigns exact locations for various circuit components within the chip's core area. An inferior placement assignment will not only affect the chip's performance but might also make it non-manufacturable by producing excessive wire-length, which is beyond available routing resources. Consequently, a placer must perform the assignment while optimizing a number of objectives to ensure that a circuit meets its performance demands. Together, the placement and routing steps of IC design are known as place and route.

In computer science and mathematical logic, satisfiability modulo theories (SMT) is the problem of determining whether a mathematical formula is satisfiable. It generalizes the Boolean satisfiability problem (SAT) to more complex formulas involving real numbers, integers, and/or various data structures such as lists, arrays, bit vectors, and strings. The name is derived from the fact that these expressions are interpreted within ("modulo") a certain formal theory in first-order logic with equality. SMT solvers are tools that aim to solve the SMT problem for a practical subset of inputs. SMT solvers such as Z3 and cvc5 have been used as a building block for a wide range of applications across computer science, including in automated theorem proving, program analysis, program verification, and software testing.

Undergraduate Texts in Mathematics (UTM) is a series of undergraduate-level textbooks in mathematics published by Springer-Verlag. The books in this series, like the other Springer-Verlag mathematics series, are small yellow books of a standard size.

<span class="mw-page-title-main">Fred W. Glover</span> American computer scientist

Fred Glover is Chief Scientific Officer of Entanglement, Inc., USA, in charge of algorithmic design and strategic planning for applications of combinatorial optimization in quantum computing. He also holds the title of Distinguished University Professor, Emeritus, at the University of Colorado, Boulder, associated with the College of Engineering and Applied Science and the Leeds School of Business. He is known for his innovations in the area of metaheuristics including the computer-based optimization methodology of Tabu search an adaptive memory programming algorithm for mathematical optimization, and the associated evolutionary Scatter Search and Path Relinking algorithms.

Eugene Leighton (Gene) Lawler was an American computer scientist and a professor of computer science at the University of California, Berkeley.

<span class="mw-page-title-main">Laurence Wolsey</span>

Laurence Alexander Wolsey is a Belgian-English mathematician working in the field of integer programming. His mother Anna Wolsey-Mautner was the daughter of the Viennese Industrialist Konrad David Mautner. He is a former president and research director of the Center for Operations Research and Econometrics (CORE) at Université catholique de Louvain in Belgium. He is professor emeritus of applied mathematics at the engineering school of the same university.

Algorithm selection is a meta-algorithmic technique to choose an algorithm from a portfolio on an instance-by-instance basis. It is motivated by the observation that on many practical problems, different algorithms have different performance characteristics. That is, while one algorithm performs well in some scenarios, it performs poorly in others and vice versa for another algorithm. If we can identify when to use which algorithm, we can optimize for each scenario and improve overall performance. This is what algorithm selection aims to do. The only prerequisite for applying algorithm selection techniques is that there exists a set of complementary algorithms.

<span class="mw-page-title-main">EvoStar</span> International evolutionary computation event

EvoStar, or Evo*, is an international scientific event devoted to evolutionary computation held in Europe. Its structure has evolved over time and it currently comprises four conferences: EuroGP the annual conference on Genetic Programming, EvoApplications, the International Conference on the Applications of Evolutionary Computation, EvoCOP, European Conference on Evolutionary Computation in Combinatorial Optimisation, and EvoMUSART, the International Conference on Computational Intelligence in Music, Sound, Art and Design. According to a 2016 study EvoApplications is a Q1 conference, while EuroGP and EvoCOP are both Q2. In 2021, EuroGP, EvoApplications and EvoCOP obtained a CORE rank B.

<span class="mw-page-title-main">Renata Mansini</span> Italian applied mathematician, economist

Renata Mansini is an Italian applied mathematician, economist, and operations researcher known for her research on problems in mathematical optimization including portfolio optimization and vehicle routing. She is a professor of operations research at the University of Brescia.

Maria Grazia Speranza is an Italian applied mathematician and operations researcher. Her research involves the application of mathematical optimization to problems including portfolio optimization and the combination of inventory management with vehicle routing.

<span class="mw-page-title-main">Tamás Terlaky</span> Hungarian mathematician (born 1955)

Tamás Terlaky is a Hungarian-Canadian-American professor of Industrial and Systems Engineering at Lehigh University. He is especially well known for his work on criss-cross algorithms, interior-point methods, Klee-Minty examples for path following algorithms, and optimization.

<span class="mw-page-title-main">Shmuel Onn</span> Israeli mathematician

Shmuel Onn is a mathematician, Professor of Operations Research and Dresner Chair at the Technion - Israel Institute of Technology. He is known for his contributions to integer programming and nonlinear combinatorial optimization.

References

  1. Mansini, Włodzimierz Ogryczak, M. Grazia Speranza - Linear and Mixed Integer Programming for Portfolio Optimization. EURO Advanced Tutorials on Operational Research. Springer. 2015. doi:10.1007/978-3-319-18482-1. ISBN   978-3-319-18481-4.
  2. Alves, C., Clautiaux, F., de Carvalho, J.V., Rietz, J. - Dual-Feasible Functions for Integer Programming and Combinatorial Optimization. EURO Advanced Tutorials on Operational Research. Springer. 2016. doi:10.1007/978-3-319-27604-5. ISBN   978-3-319-27602-1.
  3. Henggeler Antunes, Carlos, João Alves, Maria, Clímaco, João - Multiobjective Linear and Integer Programming. EURO Advanced Tutorials on Operational Research. Springer. 2016. doi:10.1007/978-3-319-28746-1. ISBN   978-3-319-28744-7.
  4. Lancia, Giuseppe, Serafini, Paolo - Compact Extended Linear Programming Model. EURO Advanced Tutorials on Operational Research. Springer. 2018. doi:10.1007/978-3-319-63976-5. ISBN   978-3-319-63975-8.
  5. Duarte, Abraham, Laguna, Manuel, Marti, Rafael - Metaheuristics for Business Analytics. EURO Advanced Tutorials on Operational Research. Springer. 2018. doi:10.1007/978-3-319-68119-1. ISBN   978-3-319-68117-7.
  6. Zhao, Lima, Huchzermeier, Arnd - Supply Chain Finance. EURO Advanced Tutorials on Operational Research. Springer. 2018. doi:10.1007/978-3-319-76663-8. ISBN   978-3-319-76662-1.
  7. van Wageningen-Kessels, Femke - Traffic Flow Modelling. EURO Advanced Tutorials on Operational Research. Springer. 2019. doi:10.1007/978-3-319-78695-7. ISBN   978-3-319-78694-0. S2CID   70279049.
  8. Doumpos, M., Lemonakis, C., Niklis, D., Zopounidis, C. - Analytical Techniques in the Assessment of Credit Risk. EURO Advanced Tutorials on Operational Research. 2019. doi:10.1007/978-3-319-99411-6. ISBN   978-3-319-99410-9. S2CID   169820038.
  9. Bigi, G., Castellani, M., Pappalardo, M., Passacantando, M. - Nonlinear Programming Techniques for Equilibria. EURO Advanced Tutorials on Operational Research. 2019. doi:10.1007/978-3-030-00205-3. ISBN   978-3-030-00204-6. S2CID   125277398.
  10. Vansteenwegen, Pieter, Gunawan, Aldy - Orienteering Problems: Models and Algorithms for Vehicle Routing Problems with Profits. EURO Advanced Tutorials on Operational Research. 2019. doi:10.1007/978-3-030-29746-6. ISBN   978-3-030-29745-9. S2CID   202789334.
  11. Fajardo, M.D., Goberna, M.A., Rodríguez, M.M.L., Vicente-Pérez, J. - Even Convexity and Optimization. EURO Advanced Tutorials on Operational Research. 2020. doi:10.1007/978-3-030-53456-1. ISBN   978-3-030-53455-4. S2CID   229215843.
  12. Menoncin, Francesco - Risk Management for Pension Funds. EURO Advanced Tutorials on Operational Research. 2021. doi:10.1007/978-3-030-55528-3. ISBN   978-3-030-55527-6.
  13. Brandimarte, Paolo - From Shortest Paths to Reinforcement Learning. EURO Advanced Tutorials on Operational Research. 2021. doi:10.1007/978-3-030-61867-4. ISBN   978-3-030-61866-7. S2CID   241626333.
  14. Maniezzo, Vittorio, Boschetti, Marco Antonio, Stützle, Thomas - Matheuristics. EURO Advanced Tutorials on Operational Research. 2021. doi:10.1007/978-3-030-70277-9. ISBN   978-3-030-70276-2. S2CID   241674620.
  15. Anjos, Miguel F., Vieira, Manuel V.C. - Facility layout. Mathematical optimization techniques and engineering. EURO Advanced Tutorials on Operational Research. Springer. 2021. doi:10.1007/978-3-030-70990-7. ISBN   978-3-030-70989-1.
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  17. Celso C. Ribeiro, Sebastian Urrutia, Dominique de Werra - Combinatorial Models for Scheduling Sports Tournaments. EURO Advanced Tutorials on Operational Research. Springer. 2023. ISBN   978-3-031-37282-7.