Humanoid ant algorithm

{{Technical|date=January 2023}}

The humanoid ant algorithm (HUMANT) {{cite journal|last1=Mladineo|first1=Marko|last2=Veza|first2=Ivica|last3=Gjeldum|first3=Nikola|title=Single-Objective and Multi-Objective Optimization using the HUMANT algorithm|journal= Croatian Operational Research Review|date=2015|volume=6|issue=2|pages=459–473|doi=10.17535/crorr.2015.0035|doi-access=free}} is an ant colony optimization algorithm. The algorithm is based on a priori approach to multi-objective optimization (MOO), which means that it integrates decision-makers preferences into optimization process.{{cite book|last1=Talbi|first1=El-Ghazali|title=Metaheuristics – From Design to Implementation|date=2009|publisher=John Wiley & Sons}} Using decision-makers preferences, it actually turns multi-objective problem into single-objective. It is a process called scalarization of a multi-objective problem.{{cite journal|last1=Eppe|first1=Stefan|title=Application of the Ant Colony Optimization Metaheuristic to multi-objective optimization problems|journal=Technical Report – ULB, Bruxelles|date=2009}} The first multi-objective ant colony optimization (MOACO) algorithm was published in 2001,{{cite journal|last1=Iredi|first1=Steffen|last2=Merkle|first2=Daniel|last3=Middendorf|first3=Martin|title=Bi-Criterion Optimization with Multi Colony Ant Algorithms|journal=Evolutionary Multi-Criterion Optimization|date=2001|volume=1993|pages=359–372|doi=10.1007/3-540-44719-9_25|series=Lecture Notes in Computer Science|isbn=978-3-540-41745-3}} but it was based on a posteriori approach to MOO.

The idea of using the preference ranking organization method for enrichment evaluation to integrate decision-makers preferences into MOACO algorithm was born in 2009.{{cite journal|last1=Eppe|first1=Stefan|title=Integrating the decision maker's preferences into Multi Objective Ant Colony Optimization|journal=Proceedings of the 2nd Doctoral Symposium on|date=2009}}

HUMANT is the only known fully operational optimization algorithm that successfully integrates PROMETHEE method into ACO.{{Citation |last=Al-Janabi |first=Rana JumaaSarih |title=Multi-key Encryption Based on RSA and Block Segmentation |date=2022 |url=http://dx.doi.org/10.1007/978-981-16-8739-6_61 |work=Biologically Inspired Techniques in Many Criteria Decision Making |pages=687–695 |access-date=2023-11-03 |place=Singapore |publisher=Springer Nature Singapore |isbn=978-981-16-8738-9 |last2=Al-Jubouri |first2=Ali Najam Mahawash}}

The HUMANT algorithm has been experimentally tested on the traveling salesman problem and applied to the partner selection problem with up to four objectives (criteria).{{cite journal|last1=Mladineo|first1=Marko|last2=Veza|first2=Ivica|last3=Gjeldum|first3=Nikola|title=Solving partner selection problem in cyber-physical production networks using the HUMANT algorithm|journal=International Journal of Production Research|volume=55|issue=9|date=2017|pages=2506–2521|doi=10.1080/00207543.2016.1234084}}