Escape from solutions stagnation. A Study on Ant System solving TSP

2019 ◽  
Vol 28 (1) ◽  
pp. 77-83
Author(s):  
CAMELIA-M. PINTEA ◽  
◽  
BARNA IANTOVICS ◽  
PETRICA POP ◽  
MATTHIAS DEHMER ◽  
...  
Keyword(s):  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Current Work ◽  
Ant System ◽  
Routing Problems ◽  
Routing Problem ◽  
The Traveling Salesman Problem ◽  
Exit State

Nowadays, routing problems arise in different contexts of distribution of goods, transportation of commodities and people. Routing problems deals with traveling along a given network in an optimal way. One of the major goals in optimization, including optimization of routing problems, is to reduce the time of stagnation by finding an exit state. The current work is a study about the ability of ants to escape from solution stagnation on a particular routing problem, the Traveling Salesman Problem.

scholarly journals ОГЛЯД ЗАВДАНЬ МАРШРУТИЗАЦІЇ, ЩО ЗВОДЯТЬСЯ ДО ЗАДАЧІ КОМІВОЯЖЕРА

2020 ◽  
pp. 152-159
Author(s):  
Ольга Борисовна Маций
Keyword(s):  
Combinatorial Optimization ◽  
Traveling Salesman Problem ◽  
Information Technologies ◽  
Traveling Salesman ◽  
Routing Problems ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
Np Complete ◽  
Modern Information ◽  
The Traveling Salesman Problem

The solution to the problem of improving the management of the transport process depends not only on the level of modernization of vehicles and the degree of use of modern information technologies, but also on the choice of routes that reduce the cost of transporting goods and passengers. Actual working conditions of vehicles in road networks put forward a number of tasks for optimizing closed routes, which are based on the classic routing problem (VRP - Vehicle Routing Problem).VRP is one of the generalizations of the hard-to-solve traveling salesman problem. The traveling salesman task is NP-complete. It refers to the main tasks of combinatorial optimization and, forming a continuously replenished set of applications and generalizations, remains an urgent research topic. An exact solution to the traveling salesman problem can be found only by reducing the enumeration of the type of branches and boundaries, which are not always applicable in operational planning by vehicle traffic. Therefore, the development of new and improvement of currently known methods for solving routing problems, reducible to the traveling salesman problem, and their software implementation is both a theoretical and practically important problem.The article considers the class of routing problems reducible to the traveling salesman problem. It is shown that optimization tasks for closed routes (routing problems), which are an important part of transport logistics, occupy key positions in the management of the processes of moving goods and passengers with the support of modern information technologies. An obvious feature that combines the considered list of routing problems (the symmetric traveling salesman problem, the problem of packing in containers, the school bus problem) is that they are formulated as generalizations or variants of the NP-complete traveling salesman problem with restrictions that narrow the scope of feasible solutions. The strongest restrictions become insufficient solvability conditions, stimulating interest in the study of combinatorial optimization problems associated with the traveling salesman problem.

The Traveling Salesman Problem, the Vehicle Routing Problem, and Their Impact on Combinatorial Optimization

2010 ◽  
Vol 1 (2) ◽  
pp. 82-92 ◽  
Author(s):  
Gilbert Laporte
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Traveling Salesman ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
The Traveling Salesman Problem

The Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP) are two of the most popular problems in the field of combinatorial optimization. Due to the study of these two problems, there has been a significant growth in families of exact and heuristic algorithms being used today. The purpose of this paper is to show how their study has fostered developments of the most popular algorithms now applied to the solution of combinatorial optimization problems. These include exact algorithms, classical heuristics and metaheuristics.

Routing

2013 ◽  
pp. 39-46 ◽  
Author(s):  
Kevin M. Curtin
Keyword(s):  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Research Area ◽  
Traveling Salesman ◽  
Heuristic Solution ◽  
Routing Problems ◽  
Shortest Path Problems ◽  
The Traveling Salesman Problem ◽  
Large Research ◽  
Routing Models

Routing is the act of selecting a course of travel. Routing problems are one of the most prominent and persistent problems in geoinformatics. This large research area has a strong theoretical foundation with ties to operations research and management science. There are a wide variety of routing models to fit many different application areas, including shortest path problems, vehicle routing problems, and the traveling salesman problem, among many others. There are also a range of optimal and heuristic solution procedures for solving instances of those problems. Research is ongoing to expand the types of routing problems that can be solved, and the environments within which they can be applied.

scholarly journals Solving the Traveling Salesman Problem with Ant Colony Optimization: A Revisit and New Efficient Algorithms

2013 ◽  
Vol 2 (3-4) ◽  
Author(s):  
Hoang Xuan Huan ◽  
Nguyen Linh-Trung ◽  
Do Duc Dong ◽  
Huu-Tue Huynh
Keyword(s):  
Ant Colony Optimization ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Ant Colony ◽  
Ant System ◽  
Benchmark Datasets ◽  
General Aspects ◽  
The Traveling Salesman Problem ◽  
Combinatoric Optimization

Ant colony optimization (ACO) techniques are known to be efficient for combinatorial optimization. The traveling salesman problem (TSP) is the benchmark used for testing new combinatoric optimization algorithms. This paper revisits the application of ACO techniques to the TSP and discuss some general aspects of ACO that have been previously overlooked. In fact, it is observed that the solution length does not reflect exactly the quality of a particular edge belong to the solution, but it is only used for relatively evaluating whether the edge is good or bad in the process of reinforcement learning. Based on this observation, we propose two algorithms– Smoothed Max-Min Ant System and Three-Level Ant System– which not only can be easily implemented but also provide better performance, as compared to the well-known Max-Min Ant System. The performance is evaluated by numerical simulation using benchmark datasets.

scholarly journals Dynamic Reduction-Expansion Operator to Improve Performance of Genetic Algorithms for the Traveling Salesman Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Diana Sanchez-Partida
Keyword(s):  
Genetic Algorithms ◽  
Traveling Salesman Problem ◽  
Nearest Neighbor ◽  
Traveling Salesman ◽  
Initial Population ◽  
Transportation Industry ◽  
Routing Problem ◽  
Population Strategy ◽  
Minimum Distances ◽  
The Traveling Salesman Problem

The Traveling Salesman Problem (TSP) is an important routing problem within the transportation industry. However, finding optimal solutions for this problem is not easy due to its computational complexity. In this work, a novel operator based on dynamic reduction-expansion of minimum distance is presented as an initial population strategy to improve the search mechanisms of Genetic Algorithms (GA) for the TSP. This operator, termed as RedExp, consists of four stages: (a) clustering to identify candidate supply/demand locations to be reduced, (b) coding of clustered and nonclustered locations to obtain the set of reduced locations, (c) sequencing of minimum distances for the set of reduced locations (nearest neighbor strategy), and (d) decoding (expansion) of the reduced set of locations. Experiments performed on TSP instances with more than 150 nodes provided evidence that RedExp can improve convergence of the GA and provide more suitable solutions than other approaches focused on the GA’s initial population.

The Traveling Salesman Problem, the Vehicle Routing Problem, and Their Impact on Combinatorial Optimization

2012 ◽  
pp. 342-352
Author(s):  
Gilbert Laporte
Keyword(s):  
Combinatorial Optimization ◽  
Vehicle Routing ◽  
Traveling Salesman Problem ◽  
Vehicle Routing Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Exact Algorithms ◽  
Traveling Salesman ◽  
Routing Problem ◽  
The Traveling Salesman Problem

The Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP) are two of the most popular problems in the field of combinatorial optimization. Due to the study of these two problems, there has been a significant growth in families of exact and heuristic algorithms being used today. The purpose of this paper is to show how their study has fostered developments of the most popular algorithms now applied to the solution of combinatorial optimization problems. These include exact algorithms, classical heuristics and metaheuristics.

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