Skip header Section
Skip Bibliometrics Section
Matheuristics: Hybridizing Metaheuristics and Mathematical ProgrammingOctober 2009
- Authors:
- Vittorio Maniezzo,
- Thomas Sttzle,
- Stefan Vo
Skip Abstract Section
Abstract
Metaheuristics support managers in decision-making with robust tools that provide high-quality solutions to important applications in business, engineering, economics, and science in reasonable time frames, but finding exact solutions in these applications still poses a real challenge. However, because of advances in the fields of mathematical optimization and metaheuristics, major efforts have been made on their interface regarding efficient hybridization. This edited book will provide a survey of the state of the art in this field by providing some invited reviews by well-known specialists as well as refereed papers from the second Matheuristics workshop to be held in Bertinoro, Italy, June 2008. Papers will explore mathematical programming techniques in metaheuristics frameworks, and especially focus on the latest developments in Mixed Integer Programming in solving real-world problems. Topics to be covered will also include dual information and metaheuristics; metaheuristics for stochastic problems; MIP solvers as search components; decompositions and lower/upper bounds in metaheuristics/MIP codes (MH codes); and real-world case histories of successful MH applications.
Cited By
- Sarhani M and Voß S (2022). Chunking and cooperation in particle swarm optimization for feature selection, Annals of Mathematics and Artificial Intelligence, 90:7-9, (893-913), Online publication date: 1-Sep-2022.
- Wu T, Zhang C, Chen W, Liang Z and Zhang X (2022). Unsupervised Learning-Driven Matheuristic for Production-Distribution Problems, Transportation Science, 56:6, (1677-1702), Online publication date: 1-Nov-2022.
- Irawan C, Wall G and Jones D (2019). An optimisation model for scheduling the decommissioning of an offshore wind farm, OR Spectrum, 41:2, (513-548), Online publication date: 1-Jun-2019.
Maniezzo V, Boschetti M, Carbonaro A, Marzolla M and Strappaveccia F (2019). Client-side Computational Optimization, ACM Transactions on Mathematical Software, 45:2, (1-16), Online publication date: 30-Jun-2019.- Alatas B (2019). Sports inspired computational intelligence algorithms for global optimization, Artificial Intelligence Review, 52:3, (1579-1627), Online publication date: 1-Oct-2019.
- Luizelli M, da Costa Cordeiro W, Buriol L and Gaspary L (2017). A fix-and-optimize approach for efficient and large scale virtual network function placement and chaining, Computer Communications, 102:C, (67-77), Online publication date: 1-Apr-2017.
- Demirovic E SAT-based approaches for the general high school timetabling problem Proceedings of the 26th International Joint Conference on Artificial Intelligence, (5175-5176)
- Li X, Wei K, Aneja Y, Tian P and Cui Y (2017). Matheuristics for the single-path design-balanced service network design problem, Computers and Operations Research, 77:C, (141-153), Online publication date: 1-Jan-2017.
- Maleki H, Khanduzi R and Akbari R (2017). A novel hybrid algorithm for solving continuous single-objective defensive location problem, Neural Computing and Applications, 28:11, (3323-3340), Online publication date: 1-Nov-2017.
- Malladi K, Mitrovic-Minic S and Punnen A (2017). Clustered maximum weight clique problem, Computers and Operations Research, 85:C, (113-128), Online publication date: 1-Sep-2017.
- Dubois-Lacoste J, Pagnozzi F and Stützle T (2017). An iterated greedy algorithm with optimization of partial solutions for the makespan permutation flowshop problem, Computers and Operations Research, 81:C, (160-166), Online publication date: 1-May-2017.
- Akyol S and Alatas B (2017). Plant intelligence based metaheuristic optimization algorithms, Artificial Intelligence Review, 47:4, (417-462), Online publication date: 1-Apr-2017.
- Hill A and Voβ S (2016). An equi-model matheuristic for the multi-depot ring star problem, Networks, 67:3, (222-237), Online publication date: 1-May-2016.
- Fonseca G, Santos H and Carrano E (2016). Integrating matheuristics and metaheuristics for timetabling, Computers and Operations Research, 74:C, (108-117), Online publication date: 1-Oct-2016.
- Yin P, Lyu S and Chuang Y (2016). Cooperative coevolutionary approach for integrated vehicle routing and scheduling using cross-dock buffering, Engineering Applications of Artificial Intelligence, 52:C, (40-53), Online publication date: 1-Jun-2016.
- Lalla-Ruiz E and Voβ S (2016). POPMUSIC as a matheuristic for the berth allocation problem, Annals of Mathematics and Artificial Intelligence, 76:1-2, (173-189), Online publication date: 1-Feb-2016.
- Schellenberg S, Li X and Michalewicz Z Benchmarks for the Coal Processing and Blending Problem Proceedings of the Genetic and Evolutionary Computation Conference 2016, (1005-1012)
- Pereira M, Coelho L, Lorena L and de Souza L (2015). A hybrid method for the Probabilistic Maximal Covering Location-Allocation Problem, Computers and Operations Research, 57:C, (51-59), Online publication date: 1-May-2015.
- Talarico L and Maya Duque P (2015). An optimization algorithm for the workforce management in a retail chain, Computers and Industrial Engineering, 82:C, (65-77), Online publication date: 1-Apr-2015.
- Gómez-Iglesias A Solving large numerical optimization problems in HPC with Python Proceedings of the 5th Workshop on Python for High-Performance and Scientific Computing, (1-8)
- Baldacci R, Boschetti M, Ganovelli M and Maniezzo V (2014). Algorithms for nesting with defects, Discrete Applied Mathematics, 163:P1, (17-33), Online publication date: 30-Jan-2014.
- Caserta M and Voíß S (2014). A hybrid algorithm for the DNA sequencing problem, Discrete Applied Mathematics, 163:P1, (87-99), Online publication date: 30-Jan-2014.
- Clautiaux F, Dell'Amico M, Iori M and Khanafer A (2014). Lower and upper bounds for the Bin Packing Problem with Fragile Objects, Discrete Applied Mathematics, 163:P1, (73-86), Online publication date: 30-Jan-2014.
- Della Croce F, Salassa F and T'kindt V (2014). A hybrid heuristic approach for single machine scheduling with release times, Computers and Operations Research, 45, (7-11), Online publication date: 1-May-2014.
- Coelho L, Cordeau J and Laporte G (2014). Heuristics for dynamic and stochastic inventory-routing, Computers and Operations Research, 52:PA, (55-67), Online publication date: 1-Dec-2014.
- Castaño F, Rossi A, Sevaux M and Velasco N (2014). A column generation approach to extend lifetime in wireless sensor networks with coverage and connectivity constraints, Computers and Operations Research, 52:PB, (220-230), Online publication date: 1-Dec-2014.
- Caserta M and Voβ S (2013). A math-heuristic Dantzig-Wolfe algorithm for capacitated lot sizing, Annals of Mathematics and Artificial Intelligence, 69:2, (207-224), Online publication date: 1-Oct-2013.
- Caserta M and Voβ S A Math-Heuristic Dantzig-Wolfe Algorithm for the Capacitated Lot Sizing Problem Revised Selected Papers of the 6th International Conference on Learning and Intelligent Optimization - Volume 7219, (31-41)
- Song B and Li V A hybridization between memetic algorithm and semidefinite relaxation for the max-cut problem Proceedings of the 14th annual conference on Genetic and evolutionary computation, (425-432)
- Croce F, Grosso A and Salassa F A matheuristic approach for the total completion time two-machines permutation flow shop problem Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization, (38-47)
- Rodríguez-Martín I and Salazar-González J The multi-commodity one-to-one pickup-and-delivery traveling salesman problem Proceedings of the 5th international conference on Network optimization, (401-405)
- Anghinolfi D, Gambardella L, Montemanni R, Nattero C, Paolucci M and Toklu N A matheuristic algorithm for a large-scale energy management problem Proceedings of the 8th international conference on Large-Scale Scientific Computing, (173-181)
- Fischetti M and Salvagnin D (2010). Pruning Moves, INFORMS Journal on Computing, 22:1, (108-119), Online publication date: 1-Jan-2010.
- Hanafi S, Lazić J, Mladenović N, Wilbaut C and Crévits I New hybrid matheuristics for solving the multidimensional knapsack problem Proceedings of the 7th international conference on Hybrid metaheuristics, (118-132)
- Caserta M and Voß S A math-heuristic algorithm for the DNA sequencing problem Proceedings of the 4th international conference on Learning and intelligent optimization, (25-36)
- Doerner K and Schmid V Survey Proceedings of the 7th international conference on Hybrid metaheuristics, (206-221)
Recommendations
Integrating matheuristics and metaheuristics for timetabling
The High School Timetabling Problem requires the assignment of times and resources to events, while sets of required and desirable constraints must be considered. The most common approach for this problem is to employ metaheuristic methods. This work ...
Matheuristics: Optimization, Simulation and Control
HM '09: Proceedings of the 6th International Workshop on Hybrid MetaheuristicsMatheuristics are heuristic algorithms made by the interoperation of metaheuristics and mathematic programming (MP) techniques. An essential feature is the exploitation in some part of the algorithms of features derived from the mathematical model of ...
Lagrangian matheuristics for the Quadratic Multiple Knapsack Problem
AbstractThe Quadratic Multiple Knapsack Problem (QMKP) is a challenging combinatorial optimization problem combining the well-known Quadratic Knapsack Problem with the Multiple Knapsack Problem. After a long stream of research devoted to ...
Highlights- First matheuristic for the Quadratic Multiple Knapsack Problem.
- Competitive ...