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Correction to: Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints

Feng Shi, Martin Schirneck, Tobias Friedrich, Timo Kötzing, Frank Neumann
2020 Algorithmica  
In the article Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints, we claimed a worst-case runtime of O(nD log D) and O(nD) for the Multi-Objective  ...  Evolutionary Algorithm and the Multi-Objective ( +( , )) Genetic Algorithm, respectively, on linear profit functions under dynamic uniform constraint, where D = |B − B * | denotes the difference between  ...  Theorem 9 The reoptimization time of the MOEA on linear functions under dynamic uniform constraint is Proof We first present the analysis for the case of B ≤ B * .  ... 
doi:10.1007/s00453-020-00739-x fatcat:e54qrl43vrehhah67fdqfjs52e

Preface to the Special Issue on Theory of Genetic and Evolutionary Computation

Carola Doerr, Dirk Sudholt
2019 Algorithmica  
One of the simplest algorithms using such a population-based approach is the (1+λ) Evolutionary Algorithm, shortly (1+λ) EA.  ...  To remedy this, theoretical computer scientists employ methods from the analysis of randomized algorithms to analyze the performance of EAs with mathematical rigor.  ...  We hope that with this special issue we further increase the interest of the general algorithms research community into evolutionary computation methods.  ... 
doi:10.1007/s00453-018-00543-8 fatcat:m5zqhwy5uvh5dntwq2uhssenfy

Fast Re-Optimization via Structural Diversity [article]

Benjamin Doerr, Carola Doerr, Frank Neumann
2019 arXiv   pre-print
We show similarly fast re-optimization times for the optimization of linear functions with changing constraints and for the minimum spanning tree problem.  ...  When started with a random Hamming neighbor of the optimum, the (1+1) evolutionary algorithm takes Ω(n^2) time to optimize the LeadingOnes benchmark function, which is the same asymptotic optimization  ...  Parts of this research has been conducted during a research visit of Frank Neumann as invited professor at Sorbonne University, with financial support from the LIP6 laboratory.  ... 
arXiv:1902.00304v1 fatcat:abir6ogl4bf5dihxljv4qxg5hu

Analysis of Evolutionary Algorithms in Dynamic and Stochastic Environments [article]

Vahid Roostapour, Mojgan Pourhassan, Frank Neumann
2018 arXiv   pre-print
We review recent theoretical studies of evolutionary algorithms and ant colony optimization for problems where the objective functions or the constraints change over time.  ...  Evolutionary algorithms and other bio-inspired algorithms have been widely applied to dynamic and stochastic problems.  ...  time of evolutionary algorithms on linear functions with a dynamic uniform constraint. flip the 0-bit whose weight is maximal.  ... 
arXiv:1806.08547v1 fatcat:owinhyd73zgv5hwxt37juzb6s4

Runtime analysis of randomized search heuristics for dynamic graph coloring

Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
2019 Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '19  
However, graph classes that are hard for one algorithm turn out to be easy for others. In most cases our bounds show that reoptimization is faster than optimizing from scratch.  ...  We contribute to the theoretical understanding of randomized search heuristics for dynamic problems.  ...  Furthermore, the behaviour of evolutionary algorithms on linear functions with dynamic constraints has been analyzed in [28] and experimental investigations for the knapsack problem with a dynamically  ... 
doi:10.1145/3321707.3321792 dblp:conf/gecco/Bossek0PS19 fatcat:qqlodxmwzncmxiyue6ef3ni4ta

Evolutionary Multi-Objective Optimization for the Dynamic Knapsack Problem [article]

Vahid Roostapour, Aneta Neumann, Frank Neumann
2020 arXiv   pre-print
In this paper, we study single- and multi-objective baseline evolutionary algorithms for the classical knapsack problem where the capacity of the knapsack varies over time.  ...  of knapsack instance under consideration.  ...  of linear functions under dynamic uniform constraints [17] .  ... 
arXiv:2004.12574v1 fatcat:fk3x77edubhafnfizigqlxqeba

Adaptive Service Composition in Flexible Processes

D. Ardagna, B. Pernici
2007 IEEE Transactions on Software Engineering  
End users can specify different preferences and constraints and service selection can be performed dynamically identifying the best set of services available at runtime.  ...  Moreover, negotiation techniques are exploited to identify a feasible solution of the problem, if one does not exist.  ...  dimension of analysis discussed above.  ... 
doi:10.1109/tse.2007.1011 fatcat:dwxitrot3fdazjdaahl7k7awjy

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191)

Carola Doerr, Christian Igel, Lothar Thiele, Xin Yao, Marc Herbstritt
2017 Dagstuhl Reports  
The meeting is the successor of the "Theory of Evolutionary Algorithm" seminar series, where the change in the title reflects the development of the research field toward a broader range of heuristics.  ...  This report summarizes the talks, breakout sessions, and discussions at the Dagstuhl Seminar 17191 on Theory of Randomized Optimization Heuristics, held during the week from May 08 until May 12, 2017,  ...  One important question is what is the reoptimization time of evolutionary algorithms, i.e. the time to recompute a good or optimal solution after a change to the constraints has happened.  ... 
doi:10.4230/dagrep.7.5.22 dblp:journals/dagstuhl-reports/DoerrIT017 fatcat:guma4eanyne6vlkwexkevs4v6i

Multi-UAV Collaborative Path Planning Method Based on Attention Mechanism

Tingzhong Wang, Binbin Zhang, Mengyan Zhang, Sen Zhang, Dongsheng Guo
2021 Mathematical Problems in Engineering  
The method draws on a combined consideration of influencing factors, such as survival probability, path length, and load balancing and endurance constraints, and works as a support system for multimachine  ...  Aiming at the problem that traditional heuristic algorithm is difficult to extract the empirical model in time from large sample terrain data, a multi-UAV collaborative path planning method based on attention  ...  of Henan Province, under Grant no. 152102210123.  ... 
doi:10.1155/2021/6964875 fatcat:iad4yvgifvarnpifoh2rs65cim

Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem

Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
2021 Algorithmica  
In most settings the expected reoptimization time for such tailored algorithms is linear in the number of added edges.  ...  The (1+1) Evolutionary Algorithm and RLS operate in a setting where the number of colors is bounded and we are minimizing the number of conflicts.  ...  Furthermore, the behaviour of evolutionary algorithms on linear functions with dynamic constraints has been analyzed in [36, 37] and experimental investigations for the knapsack problem with a dynamically  ... 
doi:10.1007/s00453-021-00838-3 fatcat:v7wq5ws7ifbcbpa7rttg4z5caa

The stochastic vehicle routing problem, a literature review, part I: models

Jorge Oyola, Halvard Arntzen, David L. Woodruff
2016 EURO Journal on Transportation and Logistics  
Building on the work of Gendreau, Laporte, and Seguin (1996), we review the past 20 years of scientific literature on stochastic vehicle routing problems (SVRP).  ...  The numerous variants of the problem that have been studied in the literature are described and categorized. Also a thorough review of solution methods applied to the SVRP is included as an Appendix.  ...  A.2.7 Evolutionary algorithms A genetic algorithm is used in Ando and Taniguchi (2006) to solve the CVRP with soft time windows and stochastic travel times.  ... 
doi:10.1007/s13676-016-0100-5 fatcat:4ap6cxp2cjdyrgohcjs7tpy55a

Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem [article]

Jakob Bossek, Frank Neumann, Pan Peng, Dirk Sudholt
2021 arXiv   pre-print
In most settings the expected reoptimization time for such tailored algorithms is linear in the number of added edges.  ...  The (1+1)~Evolutionary Algorithm and RLS operate in a setting where the number of colors is bounded and we are minimizing the number of conflicts.  ...  Furthermore, the behaviour of evolutionary algorithms on linear functions with dynamic constraints has been analyzed in [16, 17] and experimental investigations for the knapsack problem with a dynamically  ... 
arXiv:2105.12525v1 fatcat:yp5n2mxpk5gljga2jxzfmbwnla

Intelligent freight-transportation systems: Assessment and the contribution of operations research

Teodor Gabriel Crainic, Michel Gendreau, Jean-Yves Potvin
2009 Transportation Research Part C: Emerging Technologies  
On the Colombian side, many thanks also go to the Copa team and in particular to current and former members Agar, Agon, .  ...  Finally, all my gratitude goes to my all time friends Alex, Anneso, Christophe, Gwendal, Julie, Kevin, Perrine, Romain, and Yann for all the good moments shared together, for always being here, and for  ...  It captures the impact of the dynamism on the solution yield by the algorithm under analysis.  ... 
doi:10.1016/j.trc.2008.07.002 fatcat:jkpegfxkh5abhe56rcbwwqcdle

Dynamic vehicle routing: Solution methods and computational tools

Victor Pillac
2013 4OR  
Andrés Medaglia for giving me the taste of operations research in his excellent master degree course on linear programming.  ...  He taught me to de ne clear research objectives, mark the boundaries of what can be achieved in limited time, and to keep trying until things are perfect. I want to thank Dr.  ...  Finally, the constructive comments of the Editor-in-Chief, Dr. Andrew B. Whinston, and the review process of DSS led us to an improved paper.  ... 
doi:10.1007/s10288-012-0226-8 fatcat:f5jbynmrkbgf7cpcvhimskhoo4

Online Optimization: Probabilistic Analysis and Algorithm Engineering [chapter]

Benjamin Hiller
2011 Operations Research Proceedings  
The ADAC project was a good preparation for two research projects with Kollmorgen Steuerungstechnik on the development of control algorithms for passenger elevators.  ...  Before even starting in the "Combinatorial online planning" project I did already work on the project with the ADAC together with Jörg Rambau and Sven O. Krumke.  ...  Special thanks go to Tjark Vredeveld, with whom I started the analysis of the bin coloring algorithms and who always motivated me to continue the work. I am  ... 
doi:10.1007/978-3-642-20009-0_102 dblp:conf/or/Hiller10 fatcat:73xmu4ukkjcfvh7vnfoendqylq
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