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Hybrid Ant Colony Optimization Algorithm for Two Echelon Vehicle Routing Problem

Wang Meihua, Tian Xuhong, Chang shan, Wu Shumin
2011 Procedia Engineering  
Then better feasible solutions are built by an improve ant colony optimization with multiple neighborhood descent (IACO_MND), which is taken as the initial solution of the threshold-based local search  ...  A hybrid heuristic ant colony algorithm is proposed and applied to solving the two echelon vehicle routing problem, which combines three heuristic or meta-heuristics.  ...  Zhang Zebin for his programming of the algorithms.  ... 
doi:10.1016/j.proeng.2011.08.630 fatcat:zxetajgxsfatzi7qigh46hmtxu

A Study on Bio-Inspired Metaheuristics for Solving Vehicle Routing Problem

R. Yesodha, T. Amudha
2015 Indian Journal of Science and Technology  
Artificial bee colony algorithm and its application to generalized assignment problem. Swarm Intelligence: Focus on Ant and Particle Swarm Optimization. 2007 Dec; 113-45. 3.  ...  Improved ant colony optimization for seafood product delivery routing problem. Swarm Intelligence in Transportation Engineering. 2014; 26(1):1-10. 7. Chandran B, Raghavan S.  ... 
doi:10.17485/ijst/2015/v8i25/80042 fatcat:4iadtd4kenh57dfdkqtk5ido5e

Investigation of Convergence Properties of Ant Colony Based Algorithms

Anita Agárdi, László Kovács, Tamás Bányai
2019 Advanced Logistic Systems - Theory and Practice  
The paper presents the Ant Colony Optimization (ACO) algorithms, and investigates their convergence properties.  ...  Our investigation is limited to the following ACO algorithms: Ant System, MAX-MIN Ant System, Elitist Strategy of Ant System and Rank Based Version of Ant System.  ...  A literature review of Ant Colony Optimization The Ant Colony Optimization algorithms are common heuristic algorithms.  ... 
doi:10.32971/als.2020.001 fatcat:pb6yl2g7dbbsxh32o26u63dyny

Double layer programming model to the scheduling of remote sensing data processing tasks

Min-Fan He, Li-Ning Xing, Wen Li, Shang Xiang, Xu Tan
2019 Discrete and Continuous Dynamical Systems. Series S  
To solve the mathematical model, this paper presents a cooperative coevolution algorithm that combines the advantages of a very fast simulated annealing algorithm with a learnable ant colony optimization  ...  This paper presents a model using bilevel optimization, which considers task assignment and task scheduling as a single problem.  ...  Learnable ant colony optimization algorithm.  ... 
doi:10.3934/dcdss.2019104 fatcat:jt24mb6wxvcqtffrg635lfefui

Application of ant colony algorithm for vehicle routing problems

Z.A. Mereyeva, A.R. Turganbayeva
2016 International Journal of Mathematics and Physics  
Examples of such systems are ant colony [2-3], a swarm of bees [4] [5] , a flock of birds, fish, etc.  ...  This article presents the results of research and development of modification of ant algorithms for solving vehicle routing problems with a variety of verification.  ...  However, despite the primitive assignments, etc. behavior of each individual ant, the behavior of the whole colony is quite judicious [9] .  ... 
doi:10.26577/2218-7987-2016-7-1-46-49 fatcat:niojoaxj6nbhfps5qhzz2uoftq

A Hybrid GRASP+VND Heuristic for the Two-Echelon Vehicle Routing Problem Arising in City Logistics

Zheng-yang Zeng, Wei-sheng Xu, Zhi-yu Xu, Wei-hui Shao
2014 Mathematical Problems in Engineering  
Firstly, an extended split algorithm in the GRASP continuously splits randomly generated permutations of all customers and assigns customers to satellites reasonably until a feasible assignment appears  ...  The first echelons are routes that distribute freight from depot to satellites, and the second are those from satellites to customers.  ...  The authors are extremely grateful to the anonymous referees for their helpful comments.  ... 
doi:10.1155/2014/517467 fatcat:nq3qmiuskrheloelkz72nls4hy

Imperialist Competitive Algorithm with Independence and Constrained Assimilation

Ivars Dzalbs, Tatiana Kalganova, Ian Dear
2020 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)  
This work proposes an improved Imperialist Competitive Algorithm (ICA) based algorithm for solving constrained combinatorial problems, called ICA with Independence and Constrained Assimilation (ICAwICA  ...  The proposed algorithm introduces the concept of colony independence -a free will to choose between classic ICA assimilation to the empire's imperialist or any other imperialist in the population.  ...  For the comparison, the six best-performing algorithms were selected from the literature, which includes Ant Colony Optimization with Dynamic impact (ACOwD) described in [31] , Improved Whale Optimization  ... 
doi:10.1109/hora49412.2020.9152916 fatcat:usem5i265zcdpghu2pzshjvqwe

An Efficient Ant Colony System Approach for New Energy Vehicle Dispatch Problem

Di Liang, Zhi-Hui Zhan, Yanchun Zhang, Jun Zhang
2019 IEEE transactions on intelligent transportation systems (Print)  
Index Terms-New energy vehicle dispatch (NEVD), ant colony system (ACS), pre-selection, local pruning.  ...  Based on the formulated model, an efficient ant colony system (EACS) approach enhanced by pre-selection strategy and local pruning strategy is designed to dispatch NEVs to passengers.  ...  As a kind of evolutionary computation optimization algorithms, ant colony optimization (ACO) [27] is notable for its adaptability and global search capability.  ... 
doi:10.1109/tits.2019.2946711 fatcat:lujqmlqsmbfxre7ezmaymrm63i

Ant Colony Optimization [chapter]

2015 Selforganizology  
Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ...  The particular way of defining components and associated probabilities is problem-specific, and can be designed in different ways, facing a trade-off between the specificity of the information used for  ...  Introduction Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ... 
doi:10.1142/9789814699495_0009 fatcat:xyybacpzt5hqfav6ejk4njlmci

Ant Colony Algorithms For The Vehicle Routing Problem With Time Window, Period And Multiple Depots

Anita Agárdi, László Kovács, Tamás Bányai
2021 MANUFACTURING TECHNOLOGY  
The vehicles leave from one depot, visit some customers and then return to the depot. The above-described vehicle routing is solved with construction algorithms and Ant Colony algorithms.  ...  The Ant Colony algorithms are used to improve random solutions and solutions generated with construction algorithms.  ...  [28] Ant Colony Algorithms Ant Colony Optimization is one of the best known metaheuristics after Genetic Algorithm [29] , Simulated Annealing [30] and Particle Swarm Optimization [30] .  ... 
doi:10.21062/mft.2021.054 fatcat:zgbmxmw4kzgutnkbisc2dwt7bm

Ant Colony Optimization [chapter]

2013 Ant Colony Optimization and Constraint Programming  
Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ...  The particular way of defining components and associated probabilities is problem-specific, and can be designed in different ways, facing a trade-off between the specificity of the information used for  ...  Introduction Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ... 
doi:10.1002/9781118557563.part2 fatcat:nxlay2krwzd7dlgci6prhyetcm

Vehicle Routing in Multi-Echelon Distribution Systems with Cross-Docking: A Systematic Lexical-Metanarrative Analysis

Jesus Gonzalez-Feliu
2013 Computer and Information Science  
This paper presents the main concepts of multi-echelon distribution with cross-docks and the notation standards for cost optimization in this field on an attempt of unification, in order to provide a guide  ...  Multi-echelon distribution systems and more precisely, optimization of LTL routes related to them is one of the most popular subjects in the last 5 years of vehicle routing research.  ...  1500 customers).  ... 
doi:10.5539/cis.v6n3p28 fatcat:bd64wxpdmjcppmybbzhf2x7r4i

Ant Colony Optimization [chapter]

Vittorio Maniezzo, Luca Maria Gambardella, Fabio de Luigi
2004 Studies in Fuzziness and Soft Computing  
Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ...  The particular way of defining components and associated probabilities is problem-specific, and can be designed in different ways, facing a trade-off between the specificity of the information used for  ...  Introduction Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ... 
doi:10.1007/978-3-540-39930-8_5 fatcat:f7fhm7qgerb2nk2lzlxuqnh3vy

Ant Colony Optimization

2004 IEEE Transactions on Evolutionary Computation  
Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ...  The particular way of defining components and associated probabilities is problem-specific, and can be designed in different ways, facing a trade-off between the specificity of the information used for  ...  Introduction Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ... 
doi:10.1109/tevc.2004.827005 fatcat:bmgbrygudfc3phrqxpxgbwjkpy

Ant Colony Optimization [chapter]

2013 Encyclopedia of Operations Research and Management Science  
Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ...  The particular way of defining components and associated probabilities is problem-specific, and can be designed in different ways, facing a trade-off between the specificity of the information used for  ...  Introduction Ant Colony Optimization (ACO) is a paradigm for designing metaheuristic algorithms for combinatorial optimization problems.  ... 
doi:10.1007/978-1-4419-1153-7_200004 fatcat:7z6q5nh7mrbwffpon67vxlb2na
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