Results 81 to 90 of about 2,267 (186)

Heuristics and Learning Models for Dubins MinMax Traveling Salesman Problem. [PDF]

Sensors (Basel), 2023
Nayak A, Rathinam S.
europepmc   +1 more source

Comparative Study of Variations in Quantum Approximate Optimization Algorithms for the Traveling Salesman Problem. [PDF]

Entropy (Basel), 2023
Qian W, Basili RAM, Eshaghian-Wilner MM, Khokhar A, Luecke G, Vary JP.   +5 more
europepmc   +1 more source

A Parallel DNA Algorithm for Solving the Quota Traveling Salesman Problem Based on Biocomputing Model. [PDF]

Comput Intell Neurosci, 2022
Wang Z, Wu X, Wu T.
europepmc   +1 more source

Study on a hybrid algorithm combining enhanced ant colony optimization and double improved simulated annealing via clustering in the Traveling Salesman Problem (TSP). [PDF]

PeerJ Comput Sci, 2023
Hao T, Yingnian W, Jiaxing Z, Jing Z.
europepmc   +1 more source

Evaluating quantum-classical heuristics for traveling salesman problem

Discrete and Continuous Models and Applied Computational Science
In this paper, we develop and evaluate a hybrid quantum-classical heuristic approach to solving the Traveling Salesman Problem. This approach uses exhaustive enumeration of the starting paths and optimizes the remainder of the route using quantum ...
Mariia A. Makarova, Sergey V. Fedorov, Anna V. Titova, Alexander A. Khomich, Alexander S. Rumyantsev   +4 more
doaj   +1 more source

Dynamic sub-route-based self-adaptive beam search Q-learning algorithm for traveling salesman problem. [PDF]

PLoS One, 2023
Zhang J, Liu Q, Han X.
europepmc   +1 more source

Solving optimization problems simultaneously: the variants of the traveling salesman problem with time windows using multifactorial evolutionary algorithm. [PDF]

PeerJ Comput Sci, 2023
Ban HB, Pham DH.
europepmc   +1 more source

Multiple probabilistic traveling salesman problem in the coordination of drug transportation-In the context of sustainability goals and Industry 4.0. [PDF]

PLoS One, 2021
Twaróg S, Szwarc K, Wronka-Pośpiech M, Dobrowolska M, Urbanek A.   +4 more
europepmc   +1 more source

AutoRL-Sim: Automated Reinforcement Learning Simulator for Combinatorial Optimization Problems

Modelling
Reinforcement learning is a crucial area of machine learning, with a wide range of applications. To conduct experiments in this research field, it is necessary to define the algorithms and parameters to be applied.
Gleice Kelly Barbosa Souza, André Luiz Carvalho Ottoni   +1 more
doaj   +1 more source

Simultaneous Pickup and Delivery Traveling Salesman Problem considering the Express Lockers Using Attention Route Planning Network. [PDF]

Comput Intell Neurosci, 2021
Du Y, Fu S, Lu C, Zhou Q, Li C.
europepmc   +1 more source