Traveling Salesman Problem Research Papers (original) (raw)

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- Applied Mathematics, Modeling, Tabu Search, Routing

Deciding whether or not a feasible solution to the Traveling Salesman Problem with Pickups and Deliveries (TSPPD) exists is polynomially solvable. We prove that counting the number of feasible solutions of the TSPPD is hard by showing the... more

- by Geňa Hahn
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- Applied Mathematics, Combinatorics, Complexity, Optimization
- by Dorota Lipowska
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- Monte Carlo Simulation, Random Walk, Traveling Salesman Problem, Search Space
- by André Ottoni
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- Reinforcement Learning, Machine Learning, Aedes aegypti, Inteligencia artificial
- by Yan Liang
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- Engineering, Particle Swarm Optimization, Search Algorithm, Traveling Salesman Problem
- by Jan Faigl
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- Engineering, Neural Network, Path planning, Traveling Salesman Problem
- by Dr. Moshe Dror
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- Genetic Algorithms, Agriculture, Multidisciplinary, Genetic Algorithm
- by Alain Hertz
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- Applied Mathematics, Business and Management, Traveling Salesman Problem, Operations
- by Shubham Shukla
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- Traveling Salesman Problem
- by Hamza Ali
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- Computer Science, Genetic Algorithm, Traveling Salesman Problem

Groundwater long-term monitoring (LTM) is required to assess the performance of groundwater remediation and human being health risk at post-closure sites where groundwater contaminants are still present. The large number of sampling locations, number of constituents to be monitored, and the frequency of the sampling make the LTM costly, especially since LTM may be required over several decades. An optimization

- by Gary L. Lebby
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- Radio Astronomy, Genetic Algorithm, Higher Order Thinking, Machine Intelligence

This paper presents the application of 'Winner Takes All' (WTA) and Ant Colony Optimization (ACO) principles in Wang"s Recurrent Neural Network to solve the Traveling Salesman Problem. Each competing neuron is updates with a part of the value of decision variable using WTA principle. The choice of each city of the route, represented by the Neural Network neurons, is made using the ACO transition rule. The pheromones used in this new technique are the values of the decision variables of the model. The traditional WTA method uses the best value of decision matrix for each iteration. The results are compared with traditional WTA principle and others heuristics with instances of the TSPLIB (Traveling Salesman Problem Library) and 3 instances of spatial missions of debris removal. The presented results show that this new hybrid method assure equal or better results in most of the problems tested compared with traditional WTA.

The choice of an appropriate social rate of discount is critical in the decision-making process on public investments. In this paper we review the literature on social discounting, and address in particular a recently growing field of related research, that is, individual time preferences. We argue that an explicit consideration and analysis of the behaviour of individuals regarding the concept and the use of an appropriate social discount rate are essential for balanced decision making in the public sector, especially, though not exclusively, in the field of resource or environmental policy.

- by Jelke J van Hoorn
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- Weed Management, Traveling Salesman Problem, Job Shop, Complexity Analysis
- by Vladimir Deineko
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- Engineering, Mathematical Sciences, Traveling Salesman Problem, Shortest Path
- by Chiung Moon
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- Multidisciplinary, Genetic Algorithm, Optimization, Traveling Salesman Problem
- by Yeong-koo Yeo
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- Mechanical Engineering, Chemical Engineering, Korean, Profitability
- by Bengt J. Nilsson
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- Multidisciplinary, Online Algorithms, Traveling Salesman Problem, Time Dependent

Recently, it has been recognizedthat phase transitions play an important role in the proba- bilistic analysis of combinatorial optimization problems. However, there are in fact many other relations that leadto close ties between computer science andstatistical physics. This review aims at presenting the tools andconcepts d esignedby physicists to d eal with optimization or decision problems in a language accessible

- by Eranda Çela and +1
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- Combinatorial Optimization, Facility Location, Location theory, Traveling Salesman Problem
- by nisar Ahmed
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- Distributed Database, Information Technology, Genetic Algorithm, Query Optimization

Traveling Salesman Problem (TSP) is special case from assignment problem (AP) except there is a conditional restriction, Cij=∞ , if i=j. Traveling Salesman Problem has to visit n cities. In this paper we present new revised ones assignment method to solve TSP, We obtain an optimal solution for Traveling Salesman Problem by New Revised Ones Assignment Method, the results of the tests show that New Revised ones assignment is superior to some other methods such as ones assignment method, Revised Ones Assignment method. Keyword: Traveling Salesman Problem (TSP), ones assignment method, Linear integer programming.

- by Alkailany Mohammed
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- Operations Research, Traveling Salesman Problem

In packet switched computer networks, data are routed along communication links making up the network, the problem arises of how to determine the shortest paths to route the data. Each link has a cost representing the desirability of using that particular link. The shortest path then becomes the path in which the total link cost from a source node to

- by Adel Smeda
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- Computer Science, Routing algorithm, Neural Network, Computer Network
- by Gregory Gutin
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- Applied Mathematics, Reduction, Traveling Salesman Problem, Preprocessing
- by Gokhan Ozden
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- Applied Mathematics, Computer Science, Distributed Computing, Parallel Computing
- by Y. Yurramendi
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- Engineering, Genetic Algorithm, Traveling Salesman Problem, Structure learning

In this paper we introduce the balanced traveling salesman problem (BTSP), which can be used to model optimization problems where equitable distribution of resources are important. BTSP is obviously NP-hard. Efficient heuristic algorithms are presented to solve the problem along with extensive computational results using benchmark problems from TSPLIB and random instances. Our algorithms produced provably optimal solutions for several

- by Timur Keskintürk and +1
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- Traveling Salesman Problem, ANT COLONY, Travelling Salesman Problem, Shortest Path

In this paper, we present a parallel implementation of a solution for the Traveling Salesman Problem (TSP). TSP is the problem of finding the shortest path from point A to point B, given a set of points and passing through each point exactly once. Initially a sequential algorithm is fabricated from scratch and written in C language. The sequential algorithm is then converted into a parallel algorithm by integrating it with the Message Passing Interface (MPI) libraries so that it can be executed on a cluster computer. Our main aim by creating the parallel algorithm is to accelerate the execution time of solving TSP. Experimental results conducted on Beowulf cluster are presented to demonstrate the viability of our work as well as the efficiency of the parallel algorithm.

- by Shahrin Sahib and +1
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- Computer Science, System Approach, Printed Circuit Board, Traveling Salesman Problem

In this paper, we examine how the traveling salesman problem (a combinatorial optimization problem) can be used to create virtual landscapes. For this work, we show how the entire search space of ten city TSP instances can be organized into virtual landscapes, and illustrate how by changing the TSP instance problem we can control some properties of these landscapes. We provide three different methodologies for producing landscapes and show results for TSP problem instances. Our results show that our one of our methodologies generates the best aesthetically looking results and can be controlled by the problem.

- by Lindsay Grace
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- Game Design, Video Game Design, Video Game Development and Production, Videogames
- by Viet Nguyen
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- Traveling Salesman Problem

This bibliography contains 500 references on four classical routing problems: the Traveling Salesman Problem, the Vehicle Routing Problem, the Chinese Postman Problem, and the Rural Postman Problem. References are presented alphabetically... more

Travelling Salesman Problem (TSP) merupakan sebuah permasalahan optimasi yang dapat diterapkan pada berbagai kegiatan seperti routing. Masalah optimasi TSP terkenal dan telah menjadi standar untuk mencoba algoritma yang komputational. Pokok permasalahan dari TSP adalah seorang salesman harus mengunjungi sejumlah kota yang diketahui jaraknya satu dengan yang lainnya. Semua kota yang ada harus dikunjungi oleh salesman tersebut dan kota tersebut hanya boleh dikunjungi tepat satu kali. Permasalahannya adalah bagaimana salesman tersebut dapat mengatur rute perjalanannya sehingga jarak yang ditempuhnya merupakan rute yang optimum yaitu jarak minimum terbaik. Dalam makalah ini penyelesaian kasus TSP diselesaikan dengan algoritma Recursive Best First Search (RBFS).

Genetic algorithm is a widely used tool for generating searching solutions in NP-hard problems. The genetic algorithmon a particular problem should be specifically designed for parallelization and its performance gain might vary according to the parallelism hidden within the algorithm. NVIDIA GPUs that support the CUDA programming paradigm provide many processing units and a shared address space to ease the parallelization process. A heuristic genetic algorithm on the traveling salesman problem is specially designed to run on CPU. Then a corresponding CUDA program is developed for performance comparison. The experimental results indicate that a sequential genetic algorithm with intensive interactions can be accelerated by being translated into CUDA code for GPU execution.

- by Ismail Andi
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- Genetics, Parallel Processing, Genetic Algorithm, Traveling Salesman Problem

This paper presents a competitive Particle Swarm Optimization algorithm for the Traveling Salesman Problem, where the velocity operator is based upon local search and path-relinking procedures. The paper proposes two versions of the algorithm, each of them utilizing a distinct local search method. The proposed heuristics are compared with other Particle Swarm Optimization algorithms presented previously for the same problem. The results are also compared with three effective algorithms for the TSP. A computational experiment with benchmark instances is reported. The results show that the method proposed in this paper finds high quality solutions and is comparable with the effective approaches presented for the TSP.