A comprehensive survey on the Multiple Traveling Salesman Problem: Applications, approaches and taxonomy

O Cheikhrouhou, I Khoufi - Computer Science Review, 2021 - Elsevier
Abstract The Multiple Traveling Salesman Problem (MTSP) is among the most interesting
combinatorial optimization problems because it is widely adopted in real-life applications …

A review: machine learning for combinatorial optimization problems in energy areas

X Yang, Z Wang, H Zhang, N Ma, N Yang, H Liu… - Algorithms, 2022 - mdpi.com
Combinatorial optimization problems (COPs) are a class of NP-hard problems with great
practical significance. Traditional approaches for COPs suffer from high computational time …

Dec-MCTS: Decentralized planning for multi-robot active perception

G Best, OM Cliff, T Patten, RR Mettu… - … International Journal of …, 2019 - journals.sagepub.com
We propose a decentralized variant of Monte Carlo tree search (MCTS) that is suitable for a
variety of tasks in multi-robot active perception. Our algorithm allows each robot to optimize …

[HTML][HTML] A multi-agent approach to the truck multi-drone routing problem

JM Leon-Blanco, PL Gonzalez-R… - Expert Systems with …, 2022 - Elsevier
In this work, we address the Truck-multi-Drone Team Logistics Problem (TmDTL), devoted to
visit a set of points with a truck helped by a team of unmanned aerial vehicles (UAVs) or …

Socio evolution & learning optimization algorithm: A socio-inspired optimization methodology

M Kumar, AJ Kulkarni, SC Satapathy - Future Generation Computer …, 2018 - Elsevier
The paper proposes a novel metaheuristic Socio Evolution & Learning Optimization
Algorithm (SELO) inspired by the social learning behaviour of humans organized as families …

A new crossover approach for solving the multiple travelling salesmen problem using genetic algorithms

S Yuan, B Skinner, S Huang, D Liu - European journal of operational …, 2013 - Elsevier
This paper proposes a new crossover operator called two-part chromosome crossover
(TCX) for solving the multiple travelling salesmen problem (MTSP) using a genetic algorithm …

Cohort intelligence: a self supervised learning behavior

AJ Kulkarni, IP Durugkar… - 2013 IEEE international …, 2013 - ieeexplore.ieee.org
By virtue of the collective and interdependent behavior of its candidates, a swarm organizes
itself to achieve a particular task. Similarly, inspired from the natural and social tendency of …

An improved ant colony optimization algorithm for solving a complex combinatorial optimization problem

J Yang, Y Zhuang - Applied soft computing, 2010 - Elsevier
This paper presents an improved ant colony optimization algorithm (IACO) for solving mobile
agent routing problem. The ants cooperate using an indirect form of communication …

An elitist self-adaptive step-size search for structural design optimization

SK Azad, O Hasançebi - Applied Soft Computing, 2014 - Elsevier
This paper presents a method for optimal sizing of truss structures based on a refined self-
adaptive step-size search (SASS) algorithm. An elitist self-adaptive step-size search …

Cohort intelligence with self-adaptive penalty function approach hybridized with colliding bodies optimization algorithm for discrete and mixed variable constrained …

IR Kale, AJ Kulkarni - Complex & Intelligent Systems, 2021 - Springer
Abstract Recently, several socio-/bio-inspired algorithms have been proposed for solving a
variety of problems. Generally, they perform well when applied for solving unconstrained …