Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
The Stanford GraphBase: a platform for combinatorial computing
The Stanford GraphBase: a platform for combinatorial computing
A new heuristic algorithm solving the linear ordering problem
Computational Optimization and Applications
Intensification and diversification with elite tabu search solutions for the linear ordering problem
Computers and Operations Research
Tabu Search
An Experimental Evaluation of a Scatter Search for the Linear Ordering Problem
Journal of Global Optimization
The Strongest Facets of the Acyclic Subgraph Polytope Are Unknown
Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
A Hybrid GRASP with Perturbations for the Steiner Problem in Graphs
INFORMS Journal on Computing
Scatter Search: Methodology and Implementations in C
Scatter Search: Methodology and Implementations in C
Variable neighborhood search for the linear ordering problem
Computers and Operations Research
Designing a hybrid genetic algorithm for the linear ordering problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
The Linear Ordering Problem: Exact and Heuristic Methods in Combinatorial Optimization
The Linear Ordering Problem: Exact and Heuristic Methods in Combinatorial Optimization
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
A genetic programming approach for solving the linear ordering problem
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
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The linear ordering problem consists of finding an acyclic tournament in a complete weighted digraph of maximum weight. It is one of the classical NP-hard combinatorial optimization problems. This paper surveys a collection of heuristics and metaheuristic algorithms for finding near-optimal solutions and reports about extensive computational experiments with them. We also present the new benchmark library LOLIB which includes all instances previously used for this problem as well as new ones.