A review on constraint handling techniques for population-based algorithms: from single-objective to multi-objective optimization

I Rahimi, AH Gandomi, F Chen… - Archives of Computational …, 2023‏ - Springer
Most real-world problems involve some type of optimization problems that are often
constrained. Numerous researchers have investigated several techniques to deal with …

A survey on evolutionary constrained multiobjective optimization

J Liang, X Ban, K Yu, B Qu, K Qiao… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
Handling constrained multiobjective optimization problems (CMOPs) is extremely
challenging, since multiple conflicting objectives subject to various constraints require to be …

Evolutionary constrained multiobjective optimization: Test suite construction and performance comparisons

Z Ma, Y Wang - IEEE Transactions on Evolutionary …, 2019‏ - ieeexplore.ieee.org
For solving constrained multiobjective optimization problems (CMOPs), many algorithms
have been proposed in the evolutionary computation research community for the past two …

Push and pull search for solving constrained multi-objective optimization problems

Z Fan, W Li, X Cai, H Li, C Wei, Q Zhang, K Deb… - Swarm and evolutionary …, 2019‏ - Elsevier
This paper proposes a push and pull search (PPS) framework for solving constrained multi-
objective optimization problems (CMOPs). To be more specific, the proposed PPS divides …

A constrained multiobjective evolutionary algorithm with detect-and-escape strategy

Q Zhu, Q Zhang, Q Lin - IEEE Transactions on Evolutionary …, 2020‏ - ieeexplore.ieee.org
Overall constraint violation functions are commonly used in multiobjective evolutionary
algorithms (MOEAs) for handling constraints. Constraints could cause these algorithms stuck …

Shift-based penalty for evolutionary constrained multiobjective optimization and its application

Z Ma, Y Wang - IEEE Transactions on Cybernetics, 2021‏ - ieeexplore.ieee.org
This article presents a new constraint-handling technique (CHT), called shift-based penalty
(ShiP), for solving constrained multiobjective optimization problems. In ShiP, infeasible …

An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions

Z Fan, W Li, X Cai, H Huang, Y Fang, Y You, J Mo… - Soft Computing, 2019‏ - Springer
This paper proposes an improved epsilon constraint-handling mechanism and combines it
with a decomposition-based multi-objective evolutionary algorithm (MOEA/D) to solve …

Handling constrained many-objective optimization problems via problem transformation

R Jiao, S Zeng, C Li, S Yang… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Objectives optimization and constraints satisfaction are two equally important goals to solve
constrained many-objective optimization problems (CMaOPs). However, most existing …

A new fitness function with two rankings for evolutionary constrained multiobjective optimization

Z Ma, Y Wang, W Song - IEEE Transactions on Systems, Man …, 2019‏ - ieeexplore.ieee.org
Among the constraint-handling techniques (CHTs) in constrained multiobjective
optimization, constrained dominance principle (CDP) is simple, flexible, nonparametric, and …

A data-driven digital transformation approach for reverse logistics optimization in a medical waste management system

B Yaspal, SK Jauhar, S Kamble, A Belhadi… - Journal of Cleaner …, 2023‏ - Elsevier
COVID-19's aftereffects have had a significant impact on our daily lives. The recent
pandemic caused by the new coronavirus epidemic has increased the production of …