Improved Hunting Search Algorithm for the Quadratic Assignment Problem

Amine Agharghor, Mohammed Essaid Riffi, Fayçal Chebihi


Nowadays, the metaheuristics are the most studied methods used to solve the hard optimization problems. Hunting Search algorithm is a metaheuristic inspired by the method of group hunting of predatory animals like wolves. Created for solving continuous optimization problems, recently, it is adapted and evaluated to solve hard combinatorial optimization problems. This paper proposes an improved hunting search algorithm to solve the quadratic assignment problem. No local search method is used. To evaluate the performances of this work, the improved Hunting Search is checked on a set of 36 instances of QAPLib and it outperforms the results obtained by the well-known metaheuristics.


Hunting Search Algorithm; Metaheuristic; Quadratic Assignment Problem; QAPLib; Combinatorial Optimization Problem

Full Text:




  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics