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Using Swarm Intelligence for solving NP-Hard Problems

Saman Almufti
2018 Figshare  
Swarm Intelligence algorithms are computational intelligence algorithms inspired from the collectivebehavior of real swarms such as ant colony, fish school, bee colony, bat swarm, and other swarms in the  ...  This article applies most efficient heuristic based Swarm Intelligence algorithms which are Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Bat algorithm (BA), and Ant Colony Optimization  ...  Each instance is run for 100 times.Table 1shows the results of applying Particle Swarm Optimization (PSO) algorithm, Artificial Bee Colony (ABC) algorithm, Bat algorithm (BA), and Ant Colony Optimization  ... 
doi:10.6084/m9.figshare.6790445.v1 fatcat:wa27vypdkbczxgvs4i7sv2vimm

Using Swarm Intelligence for solving NPHard Problems

Saman Almufti
2017 Academic Journal of Nawroz University  
This article applies most efficient heuristic based Swarm Intelligence algorithms which are Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Bat algorithm (BA), and Ant Colony Optimization  ...  Swarm Intelligence algorithms are computational intelligence algorithms inspired from the collective behavior of real swarms such as ant colony, fish school, bee colony, bat swarm, and other swarms in  ...  Each instance is run for 100 times.Table 1shows the results of applying Particle Swarm Optimization (PSO) algorithm, Artificial Bee Colony (ABC) algorithm, Bat algorithm (BA), and Ant Colony Optimization  ... 
doi:10.25007/ajnu.v6n3a78 fatcat:zbdmbzvjtngstiezrt3xbttvu4

An Ant Colony Optimization Algorithm For Job Shop Scheduling Problem

Edson Florez, Wilfredo Gomez, MSc. Lola Bautista
2013 International Journal of Artificial Intelligence & Applications  
The nature has inspired several metaheuristics, outstanding among these is Ant Colony Optimization (ACO), which have proved to be very effective and efficient in problems of high complexity (NP-hard) in  ...  This paper describes the implementation of an ACO model algorithm known as Elitist Ant System (EAS), applied to a combinatorial optimization problem called Job Shop Scheduling Problem (JSSP).  ...  Thanks to that intelligence emerging from simple relationships between ants, a colony can solve complex problems in their environment, such as the problem of finding the shortest path between the colony  ... 
doi:10.5121/ijaia.2013.4406 fatcat:aiji7lebwvcbxj2lgkdacrdntq

A Unifying Survey of Reinforced, Sensitive and Stigmergic Agent-Based Approaches for E-GTSP [article]

Camelia-M. Pintea
2014 arXiv   pre-print
The aim of the current paper is to illustrate some variants of agent-based algorithms including ant-based models with specific properties for solving E-GTSP.  ...  The Generalized Traveling Salesman Problem (GTSP) is one of the NP-hard combinatorial optimization problems.  ...  Based on one of the best Ant Colony Optimization techniques, Ant Colony System (ACS) [13] , in [32] was first introduced, ACS for solving GTSP.  ... 
arXiv:1208.4942v2 fatcat:dme3umsnc5fi7ccddzjkotbjra

Ants can solve constraint satisfaction problems

C. Solnon
2002 IEEE Transactions on Evolutionary Computation  
In this paper, we describe a new incomplete approach for solving constraint satisfaction problems (CSPs) based on the ant colony optimization (ACO) metaheuristic.  ...  The idea is to use artificial ants to keep track of promising areas of the search space by laying trails of pheromone.  ...  Hence, a solution of a max-CSP is a complete assignment with minimal cost. In this paper, we implicitly solve max-CSPs. Artificial ants naturally solve optimization problems.  ... 
doi:10.1109/tevc.2002.802449 fatcat:rptpgsagd5cjnogbgcl5c5eam4

Solving Job Shop Scheduling Problem Using an Ant Colony Algorithm

Habibeh Nazif
2015 Journal of Asian Scientific Research  
This paper describes the implementation of an ant colony algorithm (ACA), applied to a combinatorial optimization problem called job shop scheduling problem (JSSP).  ...  The computer simulations on a set of benchmark problems are conducted to assess the merit of the proposed algorithm compared to some other heuristics in the literature.  ...  Each artificial ant starts with an empty sequence and chooses one of the jobs.  ... 
doi:10.18488/journal.2/2015.5.5/2.5.261.268 fatcat:o4hh4zjthjbxvnmx6ptgmg4vpu

A Hybrid ACO Algorithm for the Next Release Problem [article]

He Jiang, Jingyuan Zhang, Jifeng Xuan, Zhilei Ren, Yan Hu
2017 arXiv   pre-print
Inspired by the successes of Ant Colony Optimization algorithms (ACO) for solving NP-hard problems, we design our HACO to approximately solve NRP.  ...  In this paper, we propose a Hybrid Ant Colony Optimization algorithm (HACO) for Next Release Problem (NRP).  ...  Manuel Laguna for providing the latest online version of CALIBRA. Prof. Adenso-Diaz is with Computer Engineering School and Industrial Engineering School, University of Oviedo and Prof.  ... 
arXiv:1704.04777v1 fatcat:dj2emjbgtrf4djradptpih3j7i

Bio-inspired Algorithms for TSP and Generalized TSP [chapter]

Zhifeng Hao, Han Huang, Ruichu Cai
2008 Traveling Salesman Problem  
In ant colony optimization, the problem is tackled by simulating a number of artificial ants moving on a graph that encodes the problem itself.  ...  Clerc adopted discrete particle swarm optimization ( Ant colony optimization (ACO) for TSP The method of ant colony optimization solving TSP Among the bio-inspired algorithms, the ant colony optimization  ...  In this book the problem of finding algorithmic technique leading to good/optimal solutions for TSP (or for some other strictly related problems) is considered.  ... 
doi:10.5772/5583 fatcat:2wehu32nejdvviyyr5ctb7guj4

On the Resilience of an Ant-based System in Fuzzy Environments. An Empirical Study [article]

Gloria Cerasela Crisan, Camelia-M. Pintea, Petrica C. Pop
2014 arXiv   pre-print
MAX-MIN Ant System, an efficient implementation of a heuristic method is used for solving an optimization problem derived from the Traveling Salesman Problem (TSP).  ...  The entry data was adapted by introducing a two-dimensional systematic degree of fuzziness, proportional with the number of nodes, the dimension of the instance and also with the distances between nodes  ...  Based on characteristics the real ants exhibit, the Ant Colony Optimization framework describes a collection of artificial agents that cooperate and indirectly communicate in order to solve problems represented  ... 
arXiv:1401.4660v2 fatcat:mlejawjhrfb3vii6st5ednww7a

A New Mathematical Method for Solving Cuttings Transport Problem of Horizontal Wells: Ant Colony Algorithm

Liu Yongwang, Liu Yu-ming, Qiu Heng-bin, Bai Yan-feng
2017 Mathematical Problems in Engineering  
The solution-searching process of solving nonlinear equations set is transformed into an optimization process of searching the minimum value of an objective function by applying ant colony algorithm.  ...  In this paper, the ant colony algorithm is applied to solve the two-layer cuttings transport model with highly nonlinear equations set.  ...  Scholars and Innovative Research Team in University of Ministry of Education of China (no.  ... 
doi:10.1155/2017/7898647 fatcat:dxbwv6rljngdpoyum5yjl5zwuu

Ant colonies for the travelling salesman problem

Marco Dorigo, Luca Maria Gambardella
1997 Biosystems (Amsterdam. Print)  
We describe an artificial ant colony capable of solving the traveling salesman problem (TSP).  ...  Computer simulations demonstrate that the artificial ant colony is capable of generating good solutions to both symmetric and asymmetric instances of the TSP.  ...  Acknowledgments Marco Dorigo is a Research Associate with the FNRS. Luca Gambardella is Research Director at IDSIA.  ... 
doi:10.1016/s0303-2647(97)01708-5 pmid:9231906 fatcat:guyqbqxfyjdhzivwijdmymueie

A hybrid algorithm to minimize makespan for the permutation flow shop scheduling problem

Fardin Ahmadizar, Farnaz Barzinpour
2010 International Journal of Computational Intelligence Systems  
To solve this problem which has been proved to be strongly NP-hard, a combination between an ant colony algorithm, a heuristic algorithm and a local search procedure is proposed and presented.  ...  This paper deals with the permutation flow shop scheduling problem. The objective is to minimize the maximum completion time, or makespan.  ...  In recent years, ant colony optimization (ACO) algorithms have been used for solving the combinatorial optimization problems such as scheduling problems.  ... 
doi:10.1080/18756891.2010.9727747 fatcat:2whbl2lxtncjder2ywyi5ypvqm

A hybrid algorithm to minimize makespan for the permutation flow shop scheduling problem

Fardin Ahmadizar, Farnaz Barzinpour
2010 International Journal of Computational Intelligence Systems  
To solve this problem which has been proved to be strongly NP-hard, a combination between an ant colony algorithm, a heuristic algorithm and a local search procedure is proposed and presented.  ...  This paper deals with the permutation flow shop scheduling problem. The objective is to minimize the maximum completion time, or makespan.  ...  In recent years, ant colony optimization (ACO) algorithms have been used for solving the combinatorial optimization problems such as scheduling problems.  ... 
doi:10.2991/ijcis.2010.3.6.15 fatcat:n4jyjgy52rcnvgrz7qeinyyedq

Combining two pheromone structures for solving the car sequencing problem with Ant Colony Optimization

Christine Solnon
2008 European Journal of Operational Research  
In this paper, we describe an Ant Colony Optimization (ACO) algorithm for solving this problem, and we introduce two different pheromone structures for this algorithm: the first pheromone structure aims  ...  We experimentally compare these two pheromone structures, that have complementary performances, and show that their combination allows ants to solve very quickly most instances.  ...  Many thanks to Bertrand Estellon, Frédéric Gardi and Karim Nouioua for giving the code of VFLS, and to Bertrand Neveu and Gilles Trombettoni for giving the code of IDWalk.  ... 
doi:10.1016/j.ejor.2007.04.037 fatcat:uwttaoqbkbailpm4cbf7gk4afm

Page 1077 of The Journal of the Operational Research Society Vol. 59, Issue 8 [page]

2008 The Journal of the Operational Research Society  
Introduction Metaheuristics, such as Ant Colony Optimization (ACO), are widely used in the solution of combinatorial optimization problems.  ...  ° oe: , “Université Laval Ste-Foy, Québec, Canada This paper compares different ant colony optimization algorithms for solving the NP-hard car-sequencing problem, which is of great practical interest.  ... 
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