On the Nearest Neighbor Algorithms for the Traveling Salesman Problem

Kızılateş, Gözde; Nuriyeva, Fidan

doi:10.1007/978-3-319-00951-3_11

Cited by 48 publications

(25 citation statements)

References 10 publications

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“…Nearest Neighbor heuristic is perhaps the best-known tour construction heuristics [9]. It starts with a random city, adds the nearest non-visited city, and keep adding new non-visited cities in the same fashion until all cities are included.…”

Section: Tsp Heuristicsmentioning

confidence: 99%

Apple Carving Algorithm to Approximate Traveling Salesman Problem from Compact Triangulation of Planar Point Sets

Dodig¹,

Smith²

2020

IJACSA

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We propose a modified version of the Convex Hull algorithm for approximating minimum-length Hamiltonian cycle (TSP) in planar point sets. Starting from a full compact triangulation of a point set, our heuristic "carves out" candidate triangles with the minimal Triangle Inequality Measure until all points lie on the outer perimeter of the remaining partial triangulation. The initial candidate list consists of triangles on the convex hull of a given planar point set; the list is updated as triangles are eliminated and new triangles are thereby exposed. We show that the time and space complexity of the "apple carving" algorithm are O(n 2 ) and O(n), respectively. We test our algorithm using a well-known problem subset and demonstrate that our proposed algorithm outperforms nearly all other TSP tour construction heuristics.

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Section: Tsp Heuristicsmentioning

confidence: 99%

Apple Carving Algorithm to Approximate Traveling Salesman Problem from Compact Triangulation of Planar Point Sets

Dodig¹,

Smith²

2020

IJACSA

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“…Equation (5b) captures the necessary coverage constraints. For calculating the minimum traveling route, we use the Repetitive Nearest-Neighbor Algorithm [ 47 ] for calculating a Hamiltonian cycle.…”

Section: Decomposing the Problemmentioning

confidence: 99%

Global Coverage Measurement Planning Strategies for Mobile Robots Equipped with a Remote Gas Sensor

Arain

Trincavelli

Cirillo

et al. 2015

Sensors

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The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions.

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“…Finding the shortest route in large solution space (in our instance it is 64 districts of Bangladesh) using the classical TSP becomes NP-hard of combinatorial problem [23,24,25]. Among many formulations of TSP, the study use Integer Linear Programming (ILP) for exact optimal solution and Nearest Neighbor Algorithm (NNA) for near optimal solution to identify the dominance among them during emergency response by comparing results [19,25,33,40].…”

Section: Tsp Formulation and Computational Complexitymentioning

confidence: 99%

Evaluation of TSP for Emergency Routing

Zaman¹,

Hasan²,

Ulla³

2021

IJITCS

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The paper considers the symmetric traveling salesman problem and applies it to sixty-four (64) districts of Bangladesh (with geographic coordinates) as a new instance of the problem of finding an optimized route in need of emergency. It approached three different algorithms namely Integer Linear Programming, Nearest-neighbor, and Metric TSP as exact, heuristic, or approximate methods of solving the NP-hard class of problem to model the emergency route planning. These algorithms have been implanted using computer codes, used IBM ILOG CPLEX parallel optimization, visualized using Geographic Information System tools. The performance of these algorithms also has been evaluated in terms of computational complexity, their run-time, and resulted tour distance using exact, approximate, and heuristic methods to find the best fit of route optimization in emergence thus contributing to the field of combinatorial optimization.

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On the Nearest Neighbor Algorithms for the Traveling Salesman Problem

Cited by 48 publications

References 10 publications

Apple Carving Algorithm to Approximate Traveling Salesman Problem from Compact Triangulation of Planar Point Sets

Apple Carving Algorithm to Approximate Traveling Salesman Problem from Compact Triangulation of Planar Point Sets

Global Coverage Measurement Planning Strategies for Mobile Robots Equipped with a Remote Gas Sensor

Evaluation of TSP for Emergency Routing

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