Binary Cockroach Swarm Optimization for Combinatorial Optimization Problem [PDF]
Algorithms, 2016 The Cockroach Swarm Optimization (CSO) algorithm is inspired by cockroach social behavior. It is a simple and efficient meta-heuristic algorithm and has been applied to solve global optimization problems successfully.
Ibidun Christiana Obagbuwa +1 more
doaj +5 more sources
A Quantum-Inspired Tensor Network Algorithm for Constrained Combinatorial Optimization Problems [PDF]
Frontiers in Physics, 2022 Combinatorial optimization is of general interest for both theoretical study and real-world applications. Fast-developing quantum algorithms provide a different perspective on solving combinatorial optimization problems.
Tianyi Hao +5 more
doaj +2 more sources
A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems
IEEE Access, 2021 This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz.
Millie Pant, Václav Snasel
exaly +2 more sources
Conflict Resolution as a Combinatorial Optimization Problem
Information, 2023 Within the framework of the mathematical theory of conflicts, we consider a multi-criterial conflict situation using the example of a child–parent conflict.
Ekaterina Antipova, Sergey Rashkovskiy
doaj +2 more sources
Bird Mating Optimizer for Combinatorial Optimization Problems [PDF]
IEEE Access, 2020 The bird mating optimizer is a new metaheuristic algorithm that was originally proposed to solve continuous optimization problems with a very promising performance.
Anas Arram +3 more
doaj +2 more sources
Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Combinatorial optimization assumes that all parameters of the optimization problem, e.g. the weights in the objective function, are fixed. Often, these weights are mere estimates and increasingly machine learning techniques are used to for their estimation.
Mandi, Jayanta +3 more
openaire +6 more sources
The inverse k-max combinatorial optimization problem [PDF]
Yugoslav Journal of Operations Research, 2023 Classical combinatorial optimization concerns finding a feasible subset of a ground set in order to optimize an objective function. We address in this article the inverse optimization problem with the k-max function. In other words, we attempt to perturb
Nhan Tran Hoai Ngoc +3 more
doaj +1 more source
How Good is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman Problem [PDF]
IEEE Computational Intelligence Magazine, 2022 Traditional solvers for tackling combinatorial optimization (CO) problems are usually designed by human experts. Recently, there has been a surge of interest in utilizing deep learning, especially deep reinforcement learning, to automatically learn ...
Shengcai Liu, Yu Zhang, K. Tang, Xin Yao
semanticscholar +1 more source
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization [PDF]
Neural Information Processing Systems, 2023 Neural network-based Combinatorial Optimization (CO) methods have shown promising results in solving various NP-complete (NPC) problems without relying on hand-crafted domain knowledge.
Zhiqing Sun, Yiming Yang
semanticscholar +1 more source
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization [PDF]
Neural Information Processing Systems, 2023 Neural combinatorial optimization (NCO) is a promising learning-based approach for solving challenging combinatorial optimization problems without specialized algorithm design by experts.
Fu Luo +4 more
semanticscholar +1 more source