Traveling Salesman Problem
66 papers with code • 1 benchmarks • 1 datasets
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Use these libraries to find Traveling Salesman Problem models and implementationsMost implemented papers
A Powerful Genetic Algorithm for Traveling Salesman Problem
This paper presents a powerful genetic algorithm(GA) to solve the traveling salesman problem (TSP).
Evolving TSP heuristics using Multi Expression Programming
The results emphasizes that evolved MEP heuristic is a powerful tool for solving difficult TSP instances.
On the Min-cost Traveling Salesman Problem with Drone
The first algorithm (TSP-LS) was adapted from the approach proposed by Murray and Chu (2015), in which an optimal TSP solution is converted to a feasible TSP-D solution by local searches.
An Empirical Analysis of Approximation Algorithms for the Euclidean Traveling Salesman Problem
We evaluate greedy, 2-opt, and genetic algorithms.
Learning to Align the Source Code to the Compiled Object Code
We propose a new neural network architecture and use it for the task of statement-by-statement alignment of source code and its compiled object code.
Improving TSP Solutions Using GA with a New Hybrid Mutation Based on Knowledge and Randomness
The mutation operator is one of the key success factors in GA, as it is considered the exploration operator of GA.
A Hybrid Genetic Algorithm for the Traveling Salesman Problem with Drone
This paper addresses the Traveling Salesman Problem with Drone (TSP-D), in which a truck and drone are used to deliver parcels to customers.
Implementing a GPU-based parallel MAX-MIN Ant System
The results show that our MMAS implementation is competitive with state-of-the-art GPU-based and multi-core CPU-based parallel ACO implementations: in fact, the times obtained for the Nvidia V100 Volta GPU were up to 7. 18x and 21. 79x smaller, respectively.
A Non-Dominated Sorting Based Customized Random-Key Genetic Algorithm for the Bi-Objective Traveling Thief Problem
In this paper, we propose a method to solve a bi-objective variant of the well-studied Traveling Thief Problem (TTP).
Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning
We propose a policy gradient algorithm to learn a stochastic policy that selects 2-opt operations given a current solution.