Ant Colony Optimization (ACO)
|
|
- Sydney Taylor
- 8 years ago
- Views:
Transcription
1 Ant Colony Optimization (ACO) Exploits foraging behavior of ants Path optimization Problems mapping onto foraging are ACO-like TSP, ATSP QAP
2 Travelling Salesman Problem (TSP) Why? Hard, shortest path problem NP hard, in fact (no polynomial time algorithm) Well studied (can compare results to those known) GA [Freisleben and Merz] Iterated Lin-Kernighan etc. Easy to explain
3 TSP Connect n points, visiting points only once such that total path length is minimized. Path is closed; i.e. start point and end point are same. Symmetric: d = d ji It isn t easy Asymmetric: d d ji
4 TSP It s easy to create nonoptimal tours
5 Ant System (AS) for TSP Ants build tours by moving on graph Add cities one at a time until tour is complete Transition from node i to j depends on: Whether node visited (ants have a tabu list) Inverse of distance, Pheromone deposits, Transition rule: p k ( t) η =1/ d τ [ ] α τ [ η ] = [ ] α τ [ ] il ηil l k J i β β
6 Transition Equation k J i is the tabu list Constants: α, β α = 0, no cooperation, greedy search β= 0 no preference for shortest edge Note: p k (t), even though pheromone concentrations same, tabu list may be different p k ( t) = [ ] α τ [ η ] α [ τ il ] [ ηil ] l k J i β β
7 Pheromone Laying When tour complete, pheromone updated: T k (t) tour by k th ant for iteration t Q a system parameter, value is relatively unimportant = ) ( ), ( 0 ) ( ), ( ) ( / ) ( t T j i if t T j i if t L Q t k k k k τ
8 Pheromone Decay System performs poorly without pheromone decay: Saturates, local optimum found Pheromone decay: τ (0) small τ ( t) (1 ρ). τ ( t) + τ ( t) τ m k = 1 ( t) = τ k ( t)
9 Ant Density and Initial Positioning Number of ants, m, is constant for run: Too many, reinforcement too rapid Too few, pheromone decay prevents trail formation m = n found to be reasonable Initial positioning: One per node Random
10 Elitest Ants Stolen from Genetic Algorithms (GAs) Elitist ant is one which reinforces edges belonging to best tour, T + with length L + Each iteration, e elitist ants are added to other ants so that edges in T + get extra e.q/l + Improves algorithm slightly
11 Complexity and Results Time complexity: O(t.n 2.m) = O(t.n 3 ), n=m T = # iterations, n = # cities, m = # ants Initial results: Disappointing, did not match Lin-Kernighan Better for small TSP (Oliver 30 city) Rapid convergence, but only fair for 70 cities
12 Swarm Intelligence: Bonabeau et al Alg 2-1 Edge (top) initialization Ant initialization Next Edge Choice Tour Length Calculation Best tour update
13 Swarm Intelligence: Bonabeau et al Alg 2-1 (bottom) Ant pheromone updates k th Ant updates Elitest Ant updates Save new edge Pheromone values
14 Performance Results best Oliver30 Best Tour Average Std Dev. AS-TSP TS SA
15 Rapid Convergence for best tour: 1. Tends Figure to avoid 2.12 getting trapped in local optima 2. Maintains diversity in solutions as branching factor > 2 Swarm Intelligence: Bonabeau et al
16 Improvements Another transition rule: J J j arg max = u J k i, where p k ij ( t ) = k i {[ ( t) ]. [ ] } β τ η J iu l if q > iu q [ τ ( t )] [ η ] ij k J i 0 if q [ τ ( t )] [ η ] il ij β il β q 0 q uniformly distributed [0,1], q 0 is tunable
17 Observations If q > q 0, same transition as before If q q 0, make greedy choice Uses heuristic knowledge about problem: distances and pheromone trail q 0, ~1 choose locally optimal solutions q 0, ~0 all locally optimal solutions evaluated Apply Simulated Annealing to q 0
18 Swarm Intelligence: Bonabeau et al Figure 2-13 Maintains diversity Standard deviation remains high
19 Little initial pheromone, choose all edges with same probability Figure 2-14 Considerable Diversity Remains during run Swarm Intelligence: Bonabeau et al
20 Improved Pheromone Updating All ants deposit pheromone on tour completion ACS, best ant since beginning of trial updates network Encourages ants to search within vicinity of best tour found Exploration is more directed, more focussed Pheromone updates applied ONLY to edges on best path, (i,j) edges belonging to T +
21 Pheromone Updates Two forms: During creation of tour Upon tour completion by all ants
22 Pheromone Trail Updates τ ( 1 ρ ). τ ( ) + ρ. τ ( ) ( t) t t τ ( t) = 1/ L +
23 For Each Ant Transition: Local Pheromone Updates ( 1 ). ( t). 0 τ ( t) ρ τ + ρ τ τ 0 = initial value on pheromone trail Set up to be 1/(n.L nn ), L nn = length of tour found by nearest neighbor (NN) heuristic Run NN demo When ant visits an edge, the pheromone concentration decreases, making them less attractive forcing exploration of not yet visited edges. Effect of local updating is to shuffle tours. Edge desirability changes dynamically as ants visit them.
24 Candidate Lists Maintain list of preferred cities to be visited from a given city (size cl), ordered by distance Unvisited cities examined first, next city chosen according to: j J J arg max = u J k i, where p k ij ( t ) = k i {[ ( t) ]. [ ] } β τ η J iu l if q > iu q [ τ ( t )] [ η ] ij k J i 0 if q [ τ ( t )] [ η ] il ij β il β q 0
25 ACS-TSP Swarm Intelligence: Bonabeau et al Edge initialization Ant initialization Compute tour length Next Edge Choice Local Update Tour Length Calculation
26 Swarm Intelligence: Bonabeau et al Alg 2-2a Best tour update Ant pheromone Updates for best tour Save new edge Pheromone values
27 Results (25 runs) best ACS- TSP SA EN SOM 50 City (I) City (II) City (III) City (IV) City (V)
28 Results N/A N/A (N/A) N/A N/A (N/A) (N/A) ( ) KroA100 (100 cities) (N/A) (549.18) (N/A) (542.37) Eil75 (75 cities) (N/A) (427.86) (N/A) (427.96) Eil50 (50 cities) SA #iter SA best EP #iter EP best GA #iter GA best ACS- TSP #iter ACS-TSP best best
29 Adding Local Heuristics To scale, add local optimization: Works in combination with ACS For TSP, use 2-opt, 3-opt and Lin-Kernighan Eliminate 2 edges and reconnect two resulting paths to generate a different tour Run 2-opt demo
30 ACS-3-opt Same as ACS, except: Each ant tour is minimized upon tour creation For k = 1 to m do T k (t) 3-opt(T k (t)) {apply local opt to each tour} End For
31 ACS-3-opt Results (stsp) best ACS-3-opt ACS-3-opt STSP (GA) STSP (GA) Best Average Best Average d (198 cities) lin (318 cities) att (532 cities) rat (783 cities)
32 ACS-3-opt Results (atsp) best ACS-3-opt ACS-3-opt ATSP ATSP Best Average Best Average p (43 cities) ry48p (48 cities) ft (70 cities) kro124p (124 cities) ftv (170 cities)
33 Other Potential Improvements All r best ants to update trail, instead of single ant Reduce probability of being trapped in local opt. Allow β pheromone sensitivity -- to vary Remove pheromone from edges belonging to worst tours; i.e. those below average Increase convergence speed Use improved local search Several potential projects
34 Observations Pheromone concentrations vary on edges Some strongly marked, some weakly Strong on tour (likely) Weak point to alternative solutions Diversity of solutions useful in a dynamic environment We don t start from scratch Swarm may be Superior in a Dynamic environment
35 Other methods Min-Max AS [Stützle and Hoos] Iteration s best ant updates pheromone trail Pheromone concentrations limited to [τ min,τ max ] Trails initialized to τ max Bounding concentrations prevents stagnation Also, ( τ τ ( )) τ ( t) max t Strong trails reinforced less than weak Results better than AS, comparable with ACS
36 Elitest Mechanisms Bullnheimer et al Sort m ants according to tour length, L i (t) Ants update edges based upon their rank Used σ elitest ants: best σ 1 deposit trail Weighted according to max {0, σ µ} + τ ( t ) ( 1 ρ ). τ ( t ) + σ. τ ( t ) + τ ( t ) where τ τ τ + r µ ( t ) ( t ) ( t ) = = = Q / σ 1 µ = 1 L + τ ( t ) µ ( t ), µ ( σ µ ). Q / L ( t ), if ant µ uses (i, j), 0 otherwise
Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem
Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem TR/IRIDIA/1996-5 Université Libre de Bruxelles Belgium Marco Dorigo IRIDIA, Université Libre de Bruxelles, CP 194/6,
More informationSolving Traveling Salesman Problem by Using Improved Ant Colony Optimization Algorithm
Solving Traveling Salesman Problem by Using Improved Ant Colony Optimization Algorithm Zar Chi Su Su Hlaing and May Aye Khine, Member, IACSIT Abstract Ant colony optimization () is a heuristic algorithm
More informationAn ant colony optimization for single-machine weighted tardiness scheduling with sequence-dependent setups
Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization, Lisbon, Portugal, September 22-24, 2006 19 An ant colony optimization for single-machine weighted tardiness
More informationAn ACO Approach to Solve a Variant of TSP
An ACO Approach to Solve a Variant of TSP Bharat V. Chawda, Nitesh M. Sureja Abstract This study is an investigation on the application of Ant Colony Optimization to a variant of TSP. This paper presents
More informationAn Improved ACO Algorithm for Multicast Routing
An Improved ACO Algorithm for Multicast Routing Ziqiang Wang and Dexian Zhang School of Information Science and Engineering, Henan University of Technology, Zheng Zhou 450052,China wzqagent@xinhuanet.com
More informationby strong pheromone concentrations. The pheromone trail allows the ants to find their
Ant Algorithms for Discrete Optimization Marco Dorigo and Gianni Di Caro IRIDIA, Université Libre de Bruxelles Brussels, Belgium {mdorigo,gdicaro}@ulb.ac.be Luca M. Gambardella IDSIA, Lugano, Switzerland
More informationModified Ant Colony Optimization for Solving Traveling Salesman Problem
International Journal of Engineering & Computer Science IJECS-IJENS Vol:3 No:0 Modified Ant Colony Optimization for Solving Traveling Salesman Problem Abstract-- This paper presents a new algorithm for
More informationAnt colony optimization techniques for the vehicle routing problem
Advanced Engineering Informatics 18 (2004) 41 48 www.elsevier.com/locate/aei Ant colony optimization techniques for the vehicle routing problem John E. Bell a, *, Patrick R. McMullen b a Department of
More information1 ACO Algorithms for the
1 ACO Algorithms for the Traveling Salesman Problem Thomas STÜTZLE and Marco DORIGO IRIDIA, Université Libre de Bruxelles, Belgium {tstutzle,mdorigo}@ulb.ac.be 1.1 INTRODUCTION Ant algorithms [18, 14,
More informationThe ACO Encoding. Alberto Moraglio, Fernando E. B. Otero, and Colin G. Johnson
The ACO Encoding Alberto Moraglio, Fernando E. B. Otero, and Colin G. Johnson School of Computing and Centre for Reasoning, University of Kent, Canterbury, UK {A.Moraglio, F.E.B.Otero, C.G.Johnson}@kent.ac.uk
More informationSwarm Intelligence Algorithms Parameter Tuning
Swarm Intelligence Algorithms Parameter Tuning Milan TUBA Faculty of Computer Science Megatrend University of Belgrade Bulevar umetnosti 29, N. Belgrade SERBIA tuba@ieee.org Abstract: - Nature inspired
More informationDesign and Analysis of ACO algorithms for edge matching problems
Design and Analysis of ACO algorithms for edge matching problems Carl Martin Dissing Söderlind Kgs. Lyngby 2010 DTU Informatics Department of Informatics and Mathematical Modelling Technical University
More information. 1/ CHAPTER- 4 SIMULATION RESULTS & DISCUSSION CHAPTER 4 SIMULATION RESULTS & DISCUSSION 4.1: ANT COLONY OPTIMIZATION BASED ON ESTIMATION OF DISTRIBUTION ACS possesses
More informationUsing Ant Colony Optimization for Infrastructure Maintenance Scheduling
Using Ant Colony Optimization for Infrastructure Maintenance Scheduling K. Lukas, A. Borrmann & E. Rank Chair for Computation in Engineering, Technische Universität München ABSTRACT: For the optimal planning
More informationA Performance Comparison of GA and ACO Applied to TSP
A Performance Comparison of GA and ACO Applied to TSP Sabry Ahmed Haroun Laboratoire LISER, ENSEM, UH2C Casablanca, Morocco. Benhra Jamal Laboratoire LISER, ENSEM, UH2C Casablanca, Morocco. El Hassani
More informationA DISTRIBUTED APPROACH TO ANT COLONY OPTIMIZATION
A DISTRIBUTED APPROACH TO ANT COLONY OPTIMIZATION Eng. Sorin Ilie 1 Ph. D Student University of Craiova Software Engineering Department Craiova, Romania Prof. Costin Bădică Ph. D University of Craiova
More informationAn Improved Ant Colony Optimization Algorithm for Software Project Planning and Scheduling
An Improved Ant Colony Optimization Algorithm for Software Project Planning and Scheduling Avinash Mahadik Department Of Computer Engineering Alard College Of Engineering And Management,Marunje, Pune Email-avinash.mahadik5@gmail.com
More informationAn ACO-based Approach for Scheduling Task Graphs with Communication Costs
An ACO-based Approach for Scheduling Task Graphs with Communication Costs Markus Bank Udo Hönig Wolfram Schiffmann FernUniversität Hagen Lehrgebiet Rechnerarchitektur 58084 Hagen, Germany {Markus.Bank,
More informationA hybrid ACO algorithm for the Capacitated Minimum Spanning Tree Problem
A hybrid ACO algorithm for the Capacitated Minimum Spanning Tree Problem Marc Reimann Marco Laumanns Institute for Operations Research, Swiss Federal Institute of Technology Zurich, Clausiusstrasse 47,
More informationJournal of Theoretical and Applied Information Technology 20 th July 2015. Vol.77. No.2 2005-2015 JATIT & LLS. All rights reserved.
EFFICIENT LOAD BALANCING USING ANT COLONY OPTIMIZATION MOHAMMAD H. NADIMI-SHAHRAKI, ELNAZ SHAFIGH FARD, FARAMARZ SAFI Department of Computer Engineering, Najafabad branch, Islamic Azad University, Najafabad,
More informationSTUDY OF PROJECT SCHEDULING AND RESOURCE ALLOCATION USING ANT COLONY OPTIMIZATION 1
STUDY OF PROJECT SCHEDULING AND RESOURCE ALLOCATION USING ANT COLONY OPTIMIZATION 1 Prajakta Joglekar, 2 Pallavi Jaiswal, 3 Vandana Jagtap Maharashtra Institute of Technology, Pune Email: 1 somanprajakta@gmail.com,
More informationACO FOR OPTIMAL SENSOR LAYOUT
Stefka Fidanova 1, Pencho Marinov 1 and Enrique Alba 2 1 Institute for Parallel Processing, Bulgarian Academy of Science, Acad. G. Bonchev str. bl.25a, 1113 Sofia, Bulgaria 2 E.T.S.I. Informatica, Grupo
More informationRouting Optimization Heuristics Algorithms for Urban Solid Waste Transportation Management
Routing Optimization Heuristics Algorithms for Urban Solid Waste Transportation Management NIKOLAOS V. KARADIMAS, NIKOLAOS DOUKAS, MARIA KOLOKATHI, GERASIMOULA DEFTERAIOU Multimedia Technology Laboratory
More informationComparative Study: ACO and EC for TSP
Comparative Study: ACO and EC for TSP Urszula Boryczka 1 and Rafa l Skinderowicz 1 and Damian Świstowski1 1 University of Silesia, Institute of Computer Science, Sosnowiec, Poland, e-mail: uboryczk@us.edu.pl
More informationCLOUD DATABASE ROUTE SCHEDULING USING COMBANATION OF PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
CLOUD DATABASE ROUTE SCHEDULING USING COMBANATION OF PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM *Shabnam Ghasemi 1 and Mohammad Kalantari 2 1 Deparment of Computer Engineering, Islamic Azad University,
More informationFinding Liveness Errors with ACO
Hong Kong, June 1-6, 2008 1 / 24 Finding Liveness Errors with ACO Francisco Chicano and Enrique Alba Motivation Motivation Nowadays software is very complex An error in a software system can imply the
More informationTravelling Salesman Problem
Travelling Salesman Problem Travelling Salesman Problem Edited by Federico Greco I-Tech IV Published by In-Teh In-Teh is Croatian branch of I-Tech Education and Publishing KG, Vienna, Austria. Abstracting
More informationProposed Software Testing Using Intelligent techniques (Intelligent Water Drop (IWD) and Ant Colony Optimization Algorithm (ACO))
www.ijcsi.org 91 Proposed Software Testing Using Intelligent techniques (Intelligent Water Drop (IWD) and Ant Colony Optimization Algorithm (ACO)) Laheeb M. Alzubaidy 1, Baraa S. Alhafid 2 1 Software Engineering,
More informationINTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET)
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY (IJCET) International Journal of Computer Engineering and Technology (IJCET), ISSN 0976 6367(Print), ISSN 0976 6367(Print) ISSN 0976 6375(Online)
More informationAnt colonies for the traveling salesman problem
Ant colonies for the traveling salesman problem TR/IRIDIA/1996-3 Université Libre de Bruxelles Belgium Marco Dorigo IRIDIA, Université Libre de Bruxelles, Avenue Franklin Roosevelt 50, CP 194/6, 1050 Bruxelles,
More informationvii TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK
vii TABLE OF CONTENTS CHAPTER TITLE PAGE DECLARATION DEDICATION ACKNOWLEDGEMENT ABSTRACT ABSTRAK TABLE OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS LIST OF SYMBOLS LIST OF APPENDICES
More informationComputational Intelligence Algorithms for Optimized Vehicle Routing Applications in Geographic Information Systems
1 Computational Intelligence Algorithms for Optimized Vehicle Routing Applications in Geographic Information Systems Michael Rice Thesis Proposal Abstract This project seeks to explore the application
More informationParallel Ant Systems for the Capacitated Vehicle Routing Problem
Parallel Ant Systems for the Capacitated Vehicle Routing Problem Karl F. Doerner 1, Richard F. Hartl 1, Guenter Kiechle 1, Maria Lucka 2, and Marc Reimann 1,3 1 Department of Management Science, University
More informationA Study of Local Optima in the Biobjective Travelling Salesman Problem
A Study of Local Optima in the Biobjective Travelling Salesman Problem Luis Paquete, Marco Chiarandini and Thomas Stützle FG Intellektik, Technische Universität Darmstadt, Alexanderstr. 10, Darmstadt,
More informationAlpha Cut based Novel Selection for Genetic Algorithm
Alpha Cut based Novel for Genetic Algorithm Rakesh Kumar Professor Girdhar Gopal Research Scholar Rajesh Kumar Assistant Professor ABSTRACT Genetic algorithm (GA) has several genetic operators that can
More informationObtaining Optimal Software Effort Estimation Data Using Feature Subset Selection
Obtaining Optimal Software Effort Estimation Data Using Feature Subset Selection Abirami.R 1, Sujithra.S 2, Sathishkumar.P 3, Geethanjali.N 4 1, 2, 3 Student, Department of Computer Science and Engineering,
More informationDevelopment of Model-Ant Colony Optimization (ACO) in Route Selection Based on Behavioral User was Transport in Semarang, Indonesia
International Refereed Journal of Engineering and Science (IRJES) ISSN (Online) 2319-183X, (Print) 2319-1821 Volume 3, Issue 6 (June 2014), PP.09-18 Development of Model-Ant Colony Optimization (ACO) in
More informationEA and ACO Algorithms Applied to Optimizing Location of Controllers in Wireless Networks
2 EA and ACO Algorithms Applied to Optimizing Location of Controllers in Wireless Networks Dac-Nhuong Le, Hanoi University of Science, Vietnam National University, Vietnam Optimizing location of controllers
More informationHYBRID ACO-IWD OPTIMIZATION ALGORITHM FOR MINIMIZING WEIGHTED FLOWTIME IN CLOUD-BASED PARAMETER SWEEP EXPERIMENTS
HYBRID ACO-IWD OPTIMIZATION ALGORITHM FOR MINIMIZING WEIGHTED FLOWTIME IN CLOUD-BASED PARAMETER SWEEP EXPERIMENTS R. Angel Preethima 1, Margret Johnson 2 1 Student, Computer Science and Engineering, Karunya
More informationAnt colony optimization and local search for bin packing and cutting stock problems
Journal of the Operational Research Society (2004) 55, 705 716 r 2004 Operational Research Society Ltd. All rights reserved. 0160-5682/04 $30.00 www.palgrave-journals.com/jors Ant colony optimization and
More informationAn Ant Colony Optimization Approach to the Software Release Planning Problem
SBSE for Early Lifecyle Software Engineering 23 rd February 2011 London, UK An Ant Colony Optimization Approach to the Software Release Planning Problem with Dependent Requirements Jerffeson Teixeira de
More informationAnt Colony Optimization and Constraint Programming
Ant Colony Optimization and Constraint Programming Christine Solnon Series Editor Narendra Jussien WILEY Table of Contents Foreword Acknowledgements xi xiii Chapter 1. Introduction 1 1.1. Overview of the
More informationReview of Solving Software Project Scheduling Problem with Ant Colony Optimization
Review of Solving Software Project Scheduling Problem with Ant Colony Optimization K.N.Vitekar 1, S.A.Dhanawe 2, D.B.Hanchate 3 ME 2 nd Year, Dept. of Computer Engineering, VPCOE, Baramati, Pune, Maharashtra,
More informationTHE ACO ALGORITHM FOR CONTAINER TRANSPORTATION NETWORK OF SEAPORTS
THE ACO ALGORITHM FOR CONTAINER TRANSPORTATION NETWORK OF SEAPORTS Zian GUO Associate Professor School of Civil and Hydraulic Engineering Dalian University of Technology 2 Linggong Road, Ganjingzi District,
More informationAn ACO/VNS Hybrid Approach for a Large-Scale Energy Management Problem
An ACO/VNS Hybrid Approach for a Large-Scale Energy Management Problem Challenge ROADEF/EURO 2010 Roman Steiner, Sandro Pirkwieser, Matthias Prandtstetter Vienna University of Technology, Austria Institute
More informationAn ACO algorithm for image compression
An ACO algorithm for image compression Cristian Martinez University of Buenos Aires, Department of Computer Science Buenos Aires, Argentina, C1428EGA E-mail: martinezdro@yahoo.com.ar October 29, 2006 Abstract
More informationSolving Hop-constrained MST problems with ACO
n. 493 May 2013 ISSN: 0870-8541 Solving Hop-constrained MST problems with ACO Marta S.R. Monteiro 1,2 Dalila B.M.M. Fontes 1,2 Fernando A.C.C. Fontes 3,4 1 FEP-UP, School of Economics and Management, University
More informationAn Interactive Simulation and Analysis Software for Solving TSP using Ant Colony Optimization Algorithms
An Interactive Simulation and Analysis Software for Solving TSP using Ant Colony Optimization Algorithms Aybars UĞUR, Doğan AYDIN Department of Computer Engineering, University of Ege, 35100 Bornova-Izmir,
More informationA novel ACO technique for Fast and Near Optimal Solutions for the Multi-dimensional Multi-choice Knapsack Problem
A novel ACO technique for Fast and Near Optimal Solutions for the Multi-dimensional Multi-choice Knapsack Problem Shahrear Iqbal, Md. Faizul Bari, Dr. M. Sohel Rahman AlEDA Group Department of Computer
More informationACO Hypercube Framework for Solving a University Course Timetabling Problem
ACO Hypercube Framework for Solving a University Course Timetabling Problem José Miguel Rubio, Franklin Johnson and Broderick Crawford Abstract We present a resolution technique of the University course
More informationA Binary Model on the Basis of Imperialist Competitive Algorithm in Order to Solve the Problem of Knapsack 1-0
212 International Conference on System Engineering and Modeling (ICSEM 212) IPCSIT vol. 34 (212) (212) IACSIT Press, Singapore A Binary Model on the Basis of Imperialist Competitive Algorithm in Order
More informationUsing 2-Opt based evolution strategy for travelling salesman problem
An International Journal of Optimization and Control: Theories & Applications Vol.6, No.2, pp.103-113 (2016) IJOCTA ISSN: 2146-0957 eissn: 2146-5703 DOI: 10.11121/iocta.01.2016.00268 http://www.iocta.com
More informationA Proposed Scheme for Software Project Scheduling and Allocation with Event Based Scheduler using Ant Colony Optimization
A Proposed Scheme for Software Project Scheduling and Allocation with Event Based Scheduler using Ant Colony Optimization Arjita sharma 1, Niyati R Bhele 2, Snehal S Dhamale 3, Bharati Parkhe 4 NMIET,
More informationSolving the Vehicle Routing Problem with Genetic Algorithms
Solving the Vehicle Routing Problem with Genetic Algorithms Áslaug Sóley Bjarnadóttir April 2004 Informatics and Mathematical Modelling, IMM Technical University of Denmark, DTU Printed by IMM, DTU 3 Preface
More informationGenetic Algorithm Performance with Different Selection Strategies in Solving TSP
Proceedings of the World Congress on Engineering Vol II WCE, July 6-8,, London, U.K. Genetic Algorithm Performance with Different Selection Strategies in Solving TSP Noraini Mohd Razali, John Geraghty
More informationApplication Partitioning on Programmable Platforms Using the Ant Colony Optimization
Application Partitioning on Programmable Platforms Using the Ant Colony Optimization Gang Wang, Member, IEEE, Wenrui Gong, Student Member, IEEE, and Ryan Kastner, Member, IEEE Manuscript received Month
More informationDistributed Optimization by Ant Colonies
APPEARED IN PROCEEDINGS OF ECAL91 - EUROPEAN CONFERENCE ON ARTIFICIAL LIFE, PARIS, FRANCE, ELSEVIER PUBLISHING, 134 142. Distributed Optimization by Ant Colonies Alberto Colorni, Marco Dorigo, Vittorio
More informationANT COLONY OPTIMIZATION ALGORITHM FOR RESOURCE LEVELING PROBLEM OF CONSTRUCTION PROJECT
ANT COLONY OPTIMIZATION ALGORITHM FOR RESOURCE LEVELING PROBLEM OF CONSTRUCTION PROJECT Ying XIONG 1, Ya Ping KUANG 2 1. School of Economics and Management, Being Jiaotong Univ., Being, China. 2. College
More informationWireless Sensor Networks Coverage Optimization based on Improved AFSA Algorithm
, pp. 99-108 http://dx.doi.org/10.1457/ijfgcn.015.8.1.11 Wireless Sensor Networks Coverage Optimization based on Improved AFSA Algorithm Wang DaWei and Wang Changliang Zhejiang Industry Polytechnic College
More informationANT COLONY OPTIMIZATION BASED MODIFIED TERMITE ALGORITHM (MTA) WITH EFFICIENT STAGNATION AVOIDANCE STRATEGY FOR MANETS
ANT COLONY OPTIMIZATION BASED MODIFIED TERMITE ALGORITHM (MTA) WITH EFFICIENT STAGNATION AVOIDANCE STRATEGY FOR MANETS Sharvani G S, Dr. A G Ananth and Dr T M Rangaswamy R V College Of Engineering Mysore
More informationPower Plant Maintenance Scheduling Using Ant Colony Optimization
16 Power Plant Maintenance Scheduling Using Ant Colony Optimization Wai Kuan Foong, Holger Robert Maier and Angus Ross Simpson School of Civil & Environmental Engineering, University of Adelaide Australia
More informationMinimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths
Sustainability 2014, 6, 4658-4684; doi:10.3390/su6074658 Article OPEN ACCESS sustainability ISSN 2071-1050 www.mdpi.com/journal/sustainability Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet
More informationCloud database dynamic route scheduling based on polymorphic ant colony optimization algorithm
Cloud database dynamic route scheduling based on polymorphic ant colony optimization algorithm Chen Qing * Yong Zhong Liuming Xiang Chengdu Inst. of Computer Applications Chinese Academy of Science People's
More informationERSİTES ABSTRACT. The mization. a given. problem. proposed. Açgözlü. algoritma
ANADOLU ÜNİVE ERSİTES Bilim ve Teknoloji Dergisi B-Teorik Bilimler Cilt: 2 Sayı: 2 2013 Sayfa:143-148 ARAŞTIRMA MAKALESİ / RESEAR RCH ARTICLE Gözde KIZILATEŞ 1, Fidan NURİYEVA 2 A NEW HYBRID HEURISTIC
More informationBachelor Thesis Performance comparison of heuristic algorithms in routing optimization of sequencing traversing cars in a warehouse
Bachelor Thesis Performance comparison of heuristic algorithms in routing optimization of sequencing traversing cars in a warehouse Minh Hoang Technische Universität Hamburg-Harburg supervised by: Prof.
More informationOperation Scheduling: Algorithms and Applications
Chapter 13 Operation Scheduling: Algorithms and Applications Gang Wang, Wenrui Gong, and Ryan Kastner Abstract Operation scheduling (OS) is an important task in the high-level synthesis process. An inappropriate
More informationIntegrating Evolutionary Computation Components in Ant Colony Optimization
Integrating Evolutionary Computation Components in Ant Colony Optimization S. Alonso, O. Cordón, I. Fernández de Viana, F. Herrera Sergio Alonso Department of Computer Science and Artificial Intelligence
More informationLoad Balancing. Load Balancing 1 / 24
Load Balancing Backtracking, branch & bound and alpha-beta pruning: how to assign work to idle processes without much communication? Additionally for alpha-beta pruning: implementing the young-brothers-wait
More informationD A T A M I N I N G C L A S S I F I C A T I O N
D A T A M I N I N G C L A S S I F I C A T I O N FABRICIO VOZNIKA LEO NARDO VIA NA INTRODUCTION Nowadays there is huge amount of data being collected and stored in databases everywhere across the globe.
More informationAPPLICATION OF ADVANCED SEARCH- METHODS FOR AUTOMOTIVE DATA-BUS SYSTEM SIGNAL INTEGRITY OPTIMIZATION
APPLICATION OF ADVANCED SEARCH- METHODS FOR AUTOMOTIVE DATA-BUS SYSTEM SIGNAL INTEGRITY OPTIMIZATION Harald Günther 1, Stephan Frei 1, Thomas Wenzel, Wolfgang Mickisch 1 Technische Universität Dortmund,
More informationInteger Programming: Algorithms - 3
Week 9 Integer Programming: Algorithms - 3 OPR 992 Applied Mathematical Programming OPR 992 - Applied Mathematical Programming - p. 1/12 Dantzig-Wolfe Reformulation Example Strength of the Linear Programming
More informationAnt Colony Optimization for the Traveling Salesman Problem Based on Ants with Memory
Fourth International Conference on Natural Comutation Ant Colony Otimization for the Traveling Salesman Problem Based on Ants with Memory Bifan Li 1, Lio Wang 1,2, and Wu Song 3 1 College of Information
More informationInternational Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS) www.iasir.net
International Association of Scientific Innovation and Research (IASIR) (An Association Unifying the Sciences, Engineering, and Applied Research) International Journal of Emerging Technologies in Computational
More informationLoad balancing in a heterogeneous computer system by self-organizing Kohonen network
Bull. Nov. Comp. Center, Comp. Science, 25 (2006), 69 74 c 2006 NCC Publisher Load balancing in a heterogeneous computer system by self-organizing Kohonen network Mikhail S. Tarkov, Yakov S. Bezrukov Abstract.
More informationASSIGNMENT OF CONTAINER TRUCKS OF A ROAD TRANSPORT COMPANY WITH CONSIDERATION OF THE LOAD BALANCING PROBLEM
International Journal of Computer Science and Applications Technomathematics Research Foundation Vol. 10, No. 2, pp. 1 14, 2013 ASSIGNMENT OF CONTAINER TRUCKS OF A ROAD TRANSPORT COMPANY WITH CONSIDERATION
More informationANTS COLONY SYSTEM FOR SUPPLY CHAIN ROUTES OPTIMIZATION
ANTS COLONY SYSTEM FOR SUPPLY CHAIN ROUTES OPTIMIZATION G. De Sensi, F. Longo, G. Mirabelli, E. Papoff University of Calabria Via Pietro Bucci, Cube 46C, 87036 Arcavacata di Rende, Italy {g.desensi, f.longo,
More informationRunning Time Analysis of ACO Systems for Shortest Path Problems
Running Time Analysis of ACO Systems for Shortest Path Problems Christian Horoba 1 and Dirk Sudholt 1,2 1 Fakultät für Informatik, LS 2, Technische Universität Dortmund, Dortmund, Germany, lastname@ls2.cs.tu-dortmund.de
More informationGenetic Algorithms commonly used selection, replacement, and variation operators Fernando Lobo University of Algarve
Genetic Algorithms commonly used selection, replacement, and variation operators Fernando Lobo University of Algarve Outline Selection methods Replacement methods Variation operators Selection Methods
More informationSoftware Framework for Vehicle Routing Problem with Hybrid Metaheuristic Algorithms
Software Framework for Vehicle Routing Problem with Hybrid Metaheuristic Algorithms S.MASROM 1, A.M. NASIR 2 Malaysia Institute of Transport (MITRANS) Faculty of Computer and Mathematical Science Universiti
More informationInternational Journal of Emerging Technology & Research
International Journal of Emerging Technology & Research An Implementation Scheme For Software Project Management With Event-Based Scheduler Using Ant Colony Optimization Roshni Jain 1, Monali Kankariya
More informationMathematical Runtime Analysis of ACO Algorithms: Survey on an Emerging Issue
Mathematical Runtime Analysis of ACO Algorithms: Survey on an Emerging Issue Walter J. Gutjahr Department of Statistics and Decision Support Systems University of Vienna Abstract: The paper gives an overview
More informationUAV ROUTE PLANNING FOR MAXIMUM TARGET COVERAGES
UAV ROUTE PLANNING FOR MAXIMUM TARGET COVERAGES MURAT KARAKAYA 1 1 Department of Computer Engineering, Atilim University, Ankara, Turkey ABSTRACT Utilization of Unmanned Aerial Vehicles (UAVs) in military
More informationSocial Media Mining. Graph Essentials
Graph Essentials Graph Basics Measures Graph and Essentials Metrics 2 2 Nodes and Edges A network is a graph nodes, actors, or vertices (plural of vertex) Connections, edges or ties Edge Node Measures
More informationComputer Algorithms. NP-Complete Problems. CISC 4080 Yanjun Li
Computer Algorithms NP-Complete Problems NP-completeness The quest for efficient algorithms is about finding clever ways to bypass the process of exhaustive search, using clues from the input in order
More informationBeam-ACO hybridizing ant colony optimization with beam search: an application to open shop scheduling
Available online at www.sciencedirect.com Computers & Operations Research ( ) www.elsevier.com/locate/dsw Beam-ACO hybridizing ant colony optimization with beam search: an application to open shop scheduling
More informationXOR-based artificial bee colony algorithm for binary optimization
Turkish Journal of Electrical Engineering & Computer Sciences http:// journals. tubitak. gov. tr/ elektrik/ Research Article Turk J Elec Eng & Comp Sci (2013) 21: 2307 2328 c TÜBİTAK doi:10.3906/elk-1203-104
More informationStudy on Cloud Computing Resource Scheduling Strategy Based on the Ant Colony Optimization Algorithm
www.ijcsi.org 54 Study on Cloud Computing Resource Scheduling Strategy Based on the Ant Colony Optimization Algorithm Linan Zhu 1, Qingshui Li 2, and Lingna He 3 1 College of Mechanical Engineering, Zhejiang
More informationIntroduction. Swarm Intelligence - Thiemo Krink EVALife Group, Dept. of Computer Science, University of Aarhus
Swarm Intelligence - Thiemo Krink EVALife Group, Dept. of Computer Science, University of Aarhus Why do we need new computing techniques? The computer revolution changed human societies: communication
More informationMulti-Robot Traffic Planning Using ACO
Multi-Robot Traffic Planning Using ACO DR. ANUPAM SHUKLA, SANYAM AGARWAL ABV-Indian Institute of Information Technology and Management, Gwalior INDIA Sanyam.iiitm@gmail.com Abstract: - Path planning is
More informationWeb Mining using Artificial Ant Colonies : A Survey
Web Mining using Artificial Ant Colonies : A Survey Richa Gupta Department of Computer Science University of Delhi ABSTRACT : Web mining has been very crucial to any organization as it provides useful
More informationEnergy Efficiency and Maximizing Network Lifetime for WSNs using ACO Algorithm
International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-375, Volume-5 Issue-2, July 215 Energy Efficiency and Maximizing Networ Lifetime for WSNs using ACO Algorithm
More informationIterated Local Search. Variable Neighborhood Search
Iterated Local Search Variable Neighborhood Search Thomas Stützle stuetzle@informatik.tu-darmstadt.de http://www.intellektik.informatik.tu-darmstadt.de/ tom. Darmstadt University of Technology Department
More informationCloud Task Scheduling Based on Ant Colony Optimization
The International Arab Journal of Information Technology, Vol 2, No 2, March 25 29 Cloud Tas Scheduling Based on Ant Colony Optimization Medhat Tawfee, Ashraf El-Sisi, Arabi Kesh and Fawzy Torey Faculty
More informationOn the Empirical Evaluation of Las Vegas Algorithms Position Paper
On the Empirical Evaluation of Las Vegas Algorithms Position Paper Holger Hoos ½ Computer Science Department University of British Columbia Email: hoos@cs.ubc.ca Thomas Stützle IRIDIA Université Libre
More informationA CENTROID-BASED HEURISTIC ALGORITHM FOR THE CAPACITATED VEHICLE ROUTING PROBLEM
Computing and Informatics, Vol. 30, 2011, 721 732 A CENTROID-BASED HEURISTIC ALGORITHM FOR THE CAPACITATED VEHICLE ROUTING PROBLEM Kwangcheol Shin Department of Computer Science Korea Advanced Institute
More informationComputational Game Theory and Clustering
Computational Game Theory and Clustering Martin Hoefer mhoefer@mpi-inf.mpg.de 1 Computational Game Theory? 2 Complexity and Computation of Equilibrium 3 Bounding Inefficiencies 4 Conclusion Computational
More informationThe Bees Algorithm A Novel Tool for Complex Optimisation Problems
The Bees Algorithm A Novel Tool for Comple Optimisation Problems D.T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, M. Zaidi Manufacturing Engineering Centre, Cardiff University, Cardiff CF4 3AA, UK
More informationAn ACO Model for a Non-stationary Formulation of the Single Elevator Problem
An ACO Model for a Non-stationary Formulation of the Single Elevator Problem S. Molina, G. Leguizamón Universidad Nacional de San Luis, Ejército de los Andes 950, (5700) San Luis, Argentina {smolina,legui}@unsl.edu.ar
More informationBMOA: Binary Magnetic Optimization Algorithm
International Journal of Machine Learning and Computing Vol. 2 No. 3 June 22 BMOA: Binary Magnetic Optimization Algorithm SeyedAli Mirjalili and Siti Zaiton Mohd Hashim Abstract Recently the behavior of
More informationProjects - Neural and Evolutionary Computing
Projects - Neural and Evolutionary Computing 2014-2015 I. Application oriented topics 1. Task scheduling in distributed systems. The aim is to assign a set of (independent or correlated) tasks to some
More information