Ant colony optimization, survey, heuristics, co mbinatorial optimization problems. Ant colony optimization ant colony optimization is a metaheuristic inspired by the observation of real ants behavior. Parallel methods of solving of supply problem using ant. A survey of ant colony optimization algorithms for telecommunication networks. The ant colony optimization aco metaheuristic 1 is a constructive populationbased approach based on the social behavior of ants. Pdf ant colony optimization aco is a new population oriented search metaphor that has been successfully. Parallel ant colony optimization on multicore simd cpus. An efficient gpu implementation of ant colony optimization. Ant take decision with the help of special type of chemical pheromone. Download book pdf international workshop on ant colony optimization and swarm intelligence.
This paper is devoted to the presentation of a novel hybrid pseudo parallel genetic algorithm with ant colony optimization ppgaaco. This application can be formulated as a special case of the traveling salesman problem tsp. Proceedings of ppsnvi, sixth international conference on parallel problem solving from. With this article we provide a survey on theoretical results on ant colony. A survey of parallel social spider optimization algorithm. Pdf on jan 1, 2018, mohamed arezki mellal and others published a survey on ant colony optimization, particle swarm optimization, and cuckoo algorithms find, read and cite all the research you. A survey on ant inspired metaheuristic algorithmparallel. American journal of computer science and engineering survey. Using cuda, we can develop parallel algorithms to be implemented in gpus. Ant colony optimization carnegie mellon university. Proceedings of the 3rd international workshop on advanced computational intelligence, pp. Strategies for parallel ant colony optimization on. The main underlying idea, loosely inspired by the behavior of real ants, is that of a parallel search.
Ant colony optimization takes elements from real ant behavior to solve more complex problems than real ants in aco, arti. A survey paper on ant colony optimization routing algorithm for selecting multiple feasible paths for packet switched networks ms. A studyof these possibilities is intended for future r esearch, for the. Ant colony optimization techniques and applications. Base on this concept aco metaheuristic which helps to solve combinational problems such as tsp, graph color, job shop network routing, machine learning etc. Ant colony optimization aco is the best example of how studies aimed at understanding and modeling the behavior of ants and other social insects can provide inspiration for the development of computational algorithms for the solution of difficult mathematical problems. Ant colony optimization or simply aco is a meateuristic that is used to solve. A survey of recent research on optimization models and.
Ant colony optimization aco was introduced as a nature. The middle picture illustrates the situation soon after an obstacle is inserted between the nest and the food. Hybrid markov random field with parallel ant colony optimization and. The coarsegrain parallel ant colony algorithm cpaca is used to solve the problem. Ant colony optimization, survey, heuristics, combinatorial. Many swarm optimization algorithms have been introduced since the early 60s, evolutionary programming to the most recent, grey wolf optimization. These methods can be e ective for this problem, but they require a huge amount of computation long execution time, also memory consumption. Chapter 5 is a survey of current work exploiting aco to solve a variety of combi. Study of pseudoparallel genetic algorithm with ant colony. Accelerating supply chains with ant colony optimization.
In this article, we study the impact of communication when we parallelize a high performing ant colony optimization aco algorithm for the traveling salesman. Mar 18, 2014 the rapidly growing field of natureinspired computing concerns the development and application of algorithms and methods based on biological or physical principles. Genetic algorithm is an optimization algorithm that can be used to solve both minimization and maximization problem. Lucka, a parallel dant version for the vehicle routing problem, proceedings of the parallel numerics 05 2005 pp. Ant colony optimization and support vector machines 45 a method proposed to use aco algorithm for feature set selection and svm for lymph node classification from ultrasound images. Ant colony optimization is a technique for optimization that was introduced in the. If q q0, then, among the feasible components, the component that maximizes the product. Tool path optimization for computer numerical control. He has received the marie curie excellence award for his research work on ant colony optimization and ant algorithms.
Pdf this paper proposes parallelization methods of aco algorithms on a computing platform with a multicore processor aiming at fast execution to find. For books and surveys on metaheuristics see,47,56,81. Comparative analysis of ant colony and particle swarm. Parallel methods of solving of supply problem using ant colony optimization. Introduced by marco dorigo in his phd thesis 1992 and initially applied to the travelling salesman problem, the aco field. A framework for parallel ant colony optimization 1. Parallel algorithm travel salesman problem travel salesman problem message passing interface. Author links open overlay panel martin pedemonte sergio nesmachnow hector cancela.
Ant colony optimization aco is a populationbased metaheuristic for solving hard combinatorial optimization problems. In the left picture, the ants move in a straight line to the food. Particle swarm optimization pso, ant colony optimization aco are used to solve tsp. A survey of ant colony optimization with social network. Over the past decades, optimization in operations management has grown ever more popular not only in the academic literature but also in practice. Pdf ant colony optimization aco is a new population oriented search metaphor. Since you have already read up on aco, here are a few simple ideas on ways to run aco in parallel. Methodology to optimize manufacturing time for a cnc using a high performance implementation of aco regular paper oscar montielross1, nataly medinarodriguez1, roberto sepulveda1 and patricia melin2 1 instituto politecnico nacional citedi, av. In this paper, we first classify crucial optimization areas of. Oct 21, 2011 ant colony optimization aco is a populationbased metaheuristic that can be used to find approximate solutions to difficult optimization problems in aco, a set of software agents called artificial ants search for good solutions to a given optimization problem.
Selected algorithms are briefly explained and compared with each other. Ant colony optimization aco is metaheuristic algorithm inspired from nature to solve many combinatorial optimization problem such as travelling salesman. This approach is particularly compelling for practitioners in highperformance computing, as natural algorithms are often inherently parallel in nature for example, they may be based on a swarmlike model that uses a. Pdf parallelization strategics for ant colony optimization. Hybrid metaheuristics in combinatorial optimization. With this article we provide a survey on theoretical results on ant colony optimization. Ant colony optimization aco is a wellknown swarm intelligence method, inspired in the social behav ior of ant colonies for solving optimization problems.
Babita kubde2 1 cse department,rungta college of engineering and technology, bhilai, c. In 1990s, especially two approaches based on ant colony and on fish schoolingbird flocking introduced have highly attracted the interest of. This study develop an optimization model for bus transit network based on road network and zonal od. The ant colony optimization algorithm aco, introduced by marco dorigo, in the year 1992 and it is a paradigm for designing meta heuristic algorithms for optimization problems and is inspired by. This paper is devoted to the presentation of a novel hybrid pseudoparallel genetic algorithm. This paper provides an indepth survey of wellknown optimization algorithms. Comparative analysis and survey of ant colony optimization based rule miners. Among the proposed solutions, we find the use of parallel computing to. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. A survey of ant colony optimization algorithms for.
Provisional chapter parallel ant colony optimization. Ant colony optimization, genetic and evolutionary algorithms, iterated local search, simulated annealing and tabu search in alphabetical order are typical representatives of the class of metaheuristic algorithms. Ant colony optimization the ant colony systems or the basic idea of a real ant system is illustrated in figure 1. Comparative analysis and survey of ant colony optimization. Methodology to optimize manufacturing time for a cnc. A survey paper on ant colony optimization routing algorithm. In this paper a brief survey of various techniques for solving tsp using ga is given. Information sciences and technologies bulletin of the acm slovakia, vol. Ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems.
A new parallel aco model for multicoresimd cpu architecture is proposed. Methodology to optimize manufacturing time for a cnc using a. A survey paper on solving tsp using ant colony optimization. This algorithm brings an inspiration that applying similar method on ant colony optimization aco instead of ea.
Pdf survey on recent research and implementation of ant. Algorithmic models and hardware implementations pierre delisle additional information is available at the end of the chapter. Pdf parallel ant colony optimization algorithm on a multicore. Unfortunately, their results have not been satisfied at all yet. Traveling salesman problem using genetic algorithm.
Comparative evaluation of platforms for parallel ant colony. This aco exploits an optimization mechanism for solving discrete optimization problems in various engineering domains. Ant colony optimization 44 a new method using aco algorithm to segment the brain image. Pdf a survey on ant colony optimization, particle swarm.
Ant colony system aco ant colony system aco ant colony system ants in acs use thepseudorandom proportional rule probability for an ant to move from city i to city j depends on a random variable q uniformly distributed over 0. A survey on parallel ant colony optimization deteluerj. The purpose of this chapter is to present a survey of the recent developments for parallel ant colony algorithms on gpu devices, highlighting and detailing parallelism strategies for each step of an aco algorithm. A parallel proposal of ant colony optimization was used to find an optimal travel path, then the new gcodes sequence is used instead the original sequence as part of the process program. In order to overcome these weaknesses, parallel computing can be used. Ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems, finds itself currently at this point of its life cycle. Strategies for parallel ant colony optimization on graphics. Perlovsky abstract ant colony optimization is a technique for optimization that was introduced in the early 1990s. In order to study the recent contributions about parallel ant colony optimization, those papers published in the last five years 20052010 were further studied to analyze the main trends and perspectives about parallel aco implementations. Survey on recent research and implementation of ant colony optimization in. Optical and adhoc networks which fulfill the communications requirements of complex applications must meet the quality of service qos demanded by these. Pdf ant colony optimization aco takes inspiration from the foraging behaviour of real.
A survey on parallel ant colony optimization applied. In this paper we provide a survey on the ant colony optimization. Parallel ant colony optimization for the traveling salesman. The first keywords subsequent to which many variants were ant colony optimizationaco, swarm. The rapidly growing field of natureinspired computing concerns the development and application of algorithms and methods based on biological or physical principles.
Each parallel aco proposal is categorized in the new taxonomy proposed in this work. A survey on parallel ant colony optimization request pdf. The model aims at achieving minimum transfers and maximum passenger flow per unit length with line length and nonlinear rate as constraints. Ant colony optimization algorithms have been applied to many combinatorial optimization problems, ranging from quadratic assignment to protein folding or routing vehicles and a lot of derived methods have been adapted to dynamic problems in real variables, stochastic problems, multitargets and parallel implementations. Problem solving, control methods, and searchheuristic methods keywords ant colony optimization, metaheuristics, parallel algori. Request pdf a survey on parallel ant colony optimization ant colony optimization aco is a wellknown swarm intelligence method, inspired in the social behavior of ant colonies for solving. Rather than getting caught up in multiplethreads and mutlitasking, it might be helpful to think in terms of parallel compute resources at your disposal. Ant colony optimization based bioinspired hardware. A survey on parallel ant colony optimization sciencedirect.
Ant colony optimization aco is a wellknown swarm intelligence method, inspired in the social behavior of ant colonies for solving optimization problems. The first keywords subsequent to which many variants were ant colony optimization aco, swarm. Results showed that pa was able to reach a higher solution quality in fewer iterations as the number of parallel instances increased. All of these algorithms have demonstrated their potential to solve many optimization problems. Ant colony optimization and particle swarm optimization.
1081 1473 114 1345 400 797 1435 723 200 697 677 778 536 425 1453 541 1350 517 6 175 1063 494 801 1046 541 1355 428 168 218 1025 570 1465 682 240 1450 1143 363 936 852 626 1343 1345 550 1117