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Meta-Heuristic Algorithm based on Ant Colony Optimization Algorithm and Project Scheduling Problem (PSP) for the Traveling Salesman Problem
2021
International journal of computers and communications
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The Scheduling Project Ant Colony Optimization (SPANCO) Algorithm proposes a way to solve TSP problems adding three aspects: time, cost effort and scope, where the scope is the number of cities, the effort ...
The main target of Traveling Salesman Problem (TSP) is to construct the path with the lowest time between different cities, visiting every one once. ...
Tsai and Tsai [18] Describes a new approach for Solving Large Traveling Salesman Problem Using Evolutionary Ant Rules for solving TSP introducing a genetic exploitation and the method nearest neighbor ...
doi:10.46300/91013.2021.15.12
fatcat:i76rqehg25cjnlu2khhefjl3q4
An improved hybrid algorithm for capacitated fixed-charge transportation problem
2015
Logic Journal of the IGPL
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Mou, An efficient ant colony system for solving the new
generalized traveling salesman problem, in Proc. of IEEE Int. ...
Reihaneh, An Efficient Hybrid Ant Colony System for the Generalized Traveling Salesman Problem, Algorithmic Operations Research, Vol. 7, No. 1, pp. 22-29, 2012. ...
doi:10.1093/jigpal/jzv014
fatcat:6boxa6wgmzelpdg5ovbxrteebu
Survey of Metaheuristic Algorithms for Combinatorial Optimization
2012
International Journal of Computer Applications
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Population based methods deal with a set of solutions. These include genetic algorithm, ant colony optimization and particle swarm optimization. ...
This paper aims to present a brief survey of different metaheuristic algorithms for solving the combinatorial optimization problems. ...
Dorigo and Gambardella (1997) proposed a distributed algorithm ant colony system for solving traveling salesman problem. ...
doi:10.5120/9391-3813
fatcat:7ur2f64xvvb6jc4ojsd5jujfeq
Performance Evaluation of Ant Colony Systems for the Single-Depot Multiple Traveling Salesman Problem
[chapter]
2015
Lecture Notes in Computer Science
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Designed for shortest path problems and with proven efficiency for TSP, Ant Colony Systems (ACS) are a natural choice for multiple-TSP as well. ...
Derived from the well-known Traveling Salesman problem (TSP), the multiple-Traveling Salesman problem (multiple-TSP) with single depot is a straightforward generalization: several salesmen located in a ...
For large dimensions of the problem, heuristic approaches like k-opt approach [4] , or metaheuristics like Tabu Search [5] , Genetic Algorithms [6] , Ant Colony Optimization [7] , Neural Networks ...
doi:10.1007/978-3-319-19644-2_22
fatcat:7shojadqkfhvbgfc25vbvivt6u
Backbone Analysis and Applications in Heuristic Algorithm Design
2011
ACTA AUTOMATICA SINICA
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Cost Versus Distance in the Traveling Salesman Problem, Technical Report CSD-950018, University of California, USA, 1995 46 Merz P, Freisleben B. ...
As the shared common parts of all global optimal solutions to an NP-hard problem instance, the backbone has become a hot research line due to its essential impacts on the heuristic algorithm design. ...
A "memetic" approach for the traveling salesman problem implementation of a computational ecology for combinatorial optimization on messagepassing systems. ...
doi:10.3724/sp.j.1004.2011.00257
fatcat:dbvrdmoqynaulcpwrfiruateq4
Bio-inspired Algorithms for TSP and Generalized TSP
[chapter]
2008
Traveling Salesman Problem
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Ant colony optimization (ACO) for TSP Ant Colony Optimization (ACO), first proposed by M. , is a populationbased, general-purpose heuristic approach to combinational optimization problems. ...
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
Multipath Data Transmission with minimization of Congestion Using Ant Colony Optimization for MTSP and Total Queue Length
2015
International Journal of Computer Network and Information Security
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This paper represents The Ant Colony Optimization for MTSP and Swarm Inspired Multipath Data Transmission with Congestion Control in MANET using Total Queue Length based on the behavioral nature in the ...
We consider the problem of congestion control for multicast traffic in wireless networks. ...
ACKNOWLEDGMENT We thank anonymous referees for their suggestion to revise the paper. ...
doi:10.5815/ijcnis.2015.03.04
fatcat:wot6j7dzdjgqbobcp6vmpjhc6m
A comprehensive survey on the Multiple Traveling Salesman Problem: Applications, approaches and taxonomy
2021
Computer Science Review
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2021 pre-print arXiv:2102.12772v1 fatcat:stpqnliybbgkpclnpnfqyi2qg4
The Multiple Travelling Salesman Problem (MTSP) is among the most interesting combinatorial optimization problems because it is widely adopted in real-life applications, including robotics, transportation ...
Although the importance of this optimization problem, there is no survey dedicated to reviewing recent MTSP contributions. ...
ACO based approaches. The Ant colony optimization approach is a populationbased meta-heuristic to solving combinatorial optimization problems. ...
doi:10.1016/j.cosrev.2021.100369
fatcat:xnpxosxsdfbb5i6zm5ajlbx4fu
A New Multi-Objective Ant Colony Optimisation Algorithm for Solving the Quadratic Assignment Problem
2019
Vidyodaya Journal of Science
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This paper presents a new ant colony optimisation algorithm for solving multiple objective optimisation problems, and it is named as the random weight-based ant colony optimisation algorithm (RWACO). ...
The proposed algorithm is applied to the bi-objective quadratic assignment problem and evaluates the performance by comparing with some recently developed multiobjective ant colony optimisation algorithms ...
This paper proposes a new ant colony optimisation algorithm in the context of multiple objectives for solving the bi-objective quadratic assignment problem, and it is named as random weight-based ant colony ...
doi:10.4038/vjs.v22i1.6060
fatcat:ib5ay3aspvbahkibxa45zzzrvi
Survey on Recent Research and Implementation of Ant Colony Optimization in Various Engineering Applications
2011
International Journal of Computational Intelligence Systems
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Ant colony optimization (ACO) takes inspiration from the foraging behaviour of real ant species. ...
This ACO exploits a similar mechanism for solving optimization problems for the various engineering field of study. Many successful implementations using ACO are now available in many applications. ...
Xiao-ming You et al [30] proposed Parallel Ant Colony Optimization Algorithm (PQACO) based on Quantum dynamic mechanism for traveling salesman problem. ...
doi:10.2991/ijcis.2011.4.4.14
fatcat:2jss2lqp7vf53iexigpa67hopa
Survey on Recent Research and Implementation of Ant Colony Optimization in Various Engineering Applications
2011
International Journal of Computational Intelligence Systems
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Ant colony optimization (ACO) takes inspiration from the foraging behaviour of real ant species. ...
This ACO exploits a similar mechanism for solving optimization problems for the various engineering field of study. Many successful implementations using ACO are now available in many applications. ...
Xiao-ming You et al [30] proposed Parallel Ant Colony Optimization Algorithm (PQACO) based on Quantum dynamic mechanism for traveling salesman problem. ...
doi:10.1080/18756891.2011.9727813
fatcat:agxxkaaxqnhi7mrvegpalzo6ye
Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails
2010
IEEE Congress on Evolutionary Computation
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salesman problem. ...
Since probability models store global statistical information of good solutions found previously in the search, QEA have good potential to deal with hard optimization problems with many local optimal solutions ...
ANT COLONY OPTIMIZATION Ant colony optimization (ACO) [13] is a constructive meta-heuristic that mimics the behavior of ants when seeking a path between the ant colony and a source of food. ...
doi:10.1109/cec.2010.5585998
dblp:conf/cec/LiSG10
fatcat:3jscrmbkavatvnn4ute7qv3bme
A Survey of Recent Extended Variants of the Traveling Salesman and Vehicle Routing Problems for Unmanned Aerial Vehicles
2019
Drones
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These are related to the two existing general classic ones—the Traveling Salesman Problem and the Vehicle Routing Problem. ...
Generally, efficiently operating a drone can be mathematically formalized as a path optimization problem under some constraints. ...
Optimization • IGA and PSO-ACO algorithms can obtain more based Ant Colony reasonable and effective solutions for the problem of UAV Optimization path planning. algorithm (PSO-ACO) • Ant Colony Optimization ...
doi:10.3390/drones3030066
fatcat:xzvuhjuwkva45fmgmjbk3b4osm
Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem
2018
International Journal of Advanced Computer Science and Applications
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Inspired by biological evolution, this field is used to solve NP-hard optimization problems to come up with best solution. ...
In this paper, we have conducted a comparative analysis between NSGA-II, NSGA-III, SPEA-2, MOEA/D and VEGA to find out which algorithm best suited for MOTSP problems. ...
Ariyasingha and Fernando [41] conducted a review of Colony Optimization Algorithms (COA) for MOTSP for bi-objective and tetra-objective functions. ...
doi:10.14569/ijacsa.2018.090251
fatcat:2wpm55tz7rchph45cadk4usqqm
Random weight-based ant colony optimisation algorithm for the multi-objective optimisation problems
2017
International Journal of Swarm Intelligence
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Over the years, ant colony optimisation (ACO) algorithms have been proposed particularly for solving the hard combinatorial optimisation problems, such as the travelling salesman problem (TSP) and the ...
It is based on the ant colony system (ACS) algorithm and uses the random weight-based method. ...
Introduction Ant colony optimisation (ACO) is an optimisation methodology based on foraging behaviour of ant colonies. ...
doi:10.1504/ijsi.2017.082398
fatcat:hq5wscarmzai5cw4h4wuxx5stq
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