MOCO-SEARCH - Bridging the gap between exact methods and heuristics for multi-objective search


Many real-life applications deal with the optimization of complex systems, which requires extensive usage of quantitative methods. Many of these applications can be modeled as combinatorial optimization problems with several objectives. Depending of the time available, these problems can be solved by exact or heuristic approaches. Despite the advances on these two solution methods, there is currently little understanding on what they have in common and how they can be combined to solve these problems in a more effective manner. This project aims to fill this gap. The goal is to establish the link between the design principles of exact and heuristic methods, to identify features that make a problem more difficult to be solved by each method, and to improve their performance by hybridizing search strategies. Special emphasis is given to rigorous performance assessment, benchmarking, and general-purpose guidelines for the design of exact and heuristic multi-objective search.


Funded by



University of Lille

Total budget

14 400,00 €

Local budget

7 200,00 €


Combinatorial Optimization, Multiobjective Optimization, Algorithms, Heuristics

Start Date


End Date