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Editorial for the special issue on metaheuristics for combinatorial optimization

Bin Hu, Francisco Chicano
2017 Journal of Heuristics  
If there is more than one objective, we speak of multiobjective combinatorial optimization and the goal is to find a set of Pareto-optimal solutions.  ...  The goal is to find an optimal solution from a finite, but typically exponentially large set, according to an objective function.  ...  The repetition-free longest common subsequence problem is a classic NP-hard problem in bio-informatics.  ... 
doi:10.1007/s10732-017-9352-y fatcat:uyd5cl3ydrfthozcuohcqwkhza

An Introduction to Multiobjective Metaheuristics for Scheduling and Timetabling [chapter]

J. Dario Landa Silva, Edmund K. Burke, Sanja Petrovic
2004 Lecture notes in economics and mathematical systems  
the problem to a single-objective one.  ...  A number of multiobjective metaheuristics have been proposed in recent years to obtain sets of compromise solutions for multiobjective optimisation problems in a single run and without the need to convert  ...  The authors thank the anonymous referees for their feedback. Their comments helped us to substantially improve the quality of this paper and to make it more readable.  ... 
doi:10.1007/978-3-642-17144-4_4 fatcat:2xmiliorcjdftnkl47ouncnoeu

Multi-objective optimization of multicast overlays for collaborative applications

Krzysztof Rzadca, Jackson Tan Teck Yong, Anwitaman Datta
2010 Computer Networks  
We also consider the multiobjective problem in which we search for a topology that provides good trade-off between these sometimes conflicting measures.  ...  Validation of our proposed algorithms on numerous graphs shows that it is important to consider the multiobjective problem, as optimal solutions for one performance measure can be far from optimal for  ...  Comparison with Weighted Approach In our approach for the multiobjective optimization, we treated each objective separately until computing the distance dist(T ) to the ideal solution.  ... 
doi:10.1016/j.comnet.2010.05.018 fatcat:lpumbrzs6zehjb5fdbx2fhblcm

Optimal Advertising Campaign Generation for Multiple Brands Using MOGA

Peter J. Fleming, Maksim A. Pashkevich
2007 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
The classical approach to the solution of this problem is the greedy heuristic, which relies on the strength of the preceding commercial breaks when selecting the next break to add to the campaign.  ...  The paper proposes a new modified multiobjective genetic algorithm (MOGA) for the problem of optimal television (TV) advertising campaign generation for multiple brands.  ...  ACKNOWLEDGMENT The authors are grateful to the Omega Software GmbH for the data used in the case studies.  ... 
doi:10.1109/tsmcc.2007.900651 fatcat:nccjw62rhng4nbodi6dxpffpmi

Multiobjective Evolutionary Optimization of DNA Sequences for Reliable DNA Computing

S.-Y. Shin, I.-H. Lee, D. Kim, B.-T. Zhang
2005 IEEE Transactions on Evolutionary Computation  
In this paper, we formulate the DNA sequence design as a multiobjective optimization problem and solve it using a constrained multiobjective evolutionary algorithm (EA).  ...  The method is implemented into the DNA sequence design system, NACST/Seq, with a suite of sequence-analysis tools to help choose the best solutions among many alternatives.  ...  ACKNOWLEDGMENT The authors would like to thank ICT at Seoul National University who provided research facilities for this study.  ... 
doi:10.1109/tevc.2005.844166 fatcat:yfqmssekuvbazf37f5uszubtsq

Multidimensional Compromise Optimization For Development Ranking Of The Gulf Cooperation Council Countries And Turkey

C. Ardil
2018 Zenodo  
The multiobjective optimization decision making problem is considered in three sequential steps.  ...  The proposed approach presents ranking solutions resulting from different multicriteria decision analyses, which yield different ranking orders for the same ranking problem, consisting of a set of alternatives  ...  Therefore, it is common to directly or indirectly search for a set of Pareto efficient solutions, and apply set oriented search procedures for multiobjective optimization analysis [28] .  ... 
doi:10.5281/zenodo.1317253 fatcat:x5xbpg3orbfz5izbc7pfq2f2xi

A Decomposition and Dominance-Based Multiobjective Artificial Bee Colony Algorithm for Multiple Sequence Alignment

Lei Ye, Jianhui Lv
2022 Mobile Information Systems  
A nondominated sorting-based onlooker strategy searches for the solutions near the Pareto front (PF) to guide the subsequent searching.  ...  MOABC/D-MSA uses three kinds of searching strategies to obtain a group of nondominated solutions with high quality and diversity of an MSA problem.  ...  to align subsequences.  ... 
doi:10.1155/2022/5444055 fatcat:2pmklqflsfe37gld3f4h6g3lta

Automated Cable Road Layout and Harvesting Planning for Multiple Objectives in Steep Terrain

Bont, Maurer, Breschan
2019 Forests  
To overcome these shortcomings, we present: (1) a multiobjective optimization approach that leads to realistic, practicable results that consider multiple conflicting design objectives, and (2) a concept  ...  The study produced the following major findings: (1) Single-objective alternatives have no practical relevance, whereas multiobjective alternatives are preferable in real-world applications and lead to  ...  Acknowledgments: We thank Roberto Bolgè from the Federal Office for the Environment (FOEN) for support for this project.  ... 
doi:10.3390/f10080687 fatcat:hmeowuydqjgjxk5fn26vh4sv3m

Evolution and Quality Analysis Algorithm of Consumer Online Reviews Based on Data Fusion and Multiobjective Optimization

Hu Wang, Tianbao Liang, Yanxia Cheng, Mu Zhou
2021 Journal of Sensors  
Description, the longest of is reached 612 words.  ...  , algorithm design method, and multiobject research method to collect samples, analyze the technical model, and streamline the algorithm.  ...  Conflicts of Interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.  ... 
doi:10.1155/2021/6252425 fatcat:dzuyrajetbevriglpk2nz4iuqu

Multiobjective Hybrid Genetic Algorithms for Manufacturing Scheduling: Part II Case Studies of HDD and TFT-LCD [chapter]

Mitsuo Gen, Wenqiang Zhang, Lin Lin
2015 Advances in Intelligent Systems and Computing  
This paper introduces how to design Mo-HGAs for solving the practical multiobjective manufacturing scheduling problems expanded by a multiobjective flexible job-shop scheduling problem (Mo-FJSP; operation  ...  In this paper, we introduce how to design hybrid genetic algorithms (HGA) and multiobjective hybrid genetic algorithms (Mo-HGA) for solving practical manufacturing scheduling problems for the hard disc  ...  The VND approach is employed to sequentially identify and exchange critical operations and find a new schedule that exhibits a small makespan in the multiobjective module assembly scheduling problem.  ... 
doi:10.1007/978-3-662-47241-5_2 fatcat:cta4yo5jwfdgnm63iuynxe6d2u

Bicriteria Optimization in Wireless Sensor Networks: Link Scheduling and Energy Consumption

Jian Chen, Jie Jia, Enliang Dai, Yingyou Wen, Dazhe Zhao
2015 Journal of Sensors  
As a contribution, by jointly modeling the route selection and interference-free link scheduling problem, we give a systematical analysis on the relationship between link scheduling and energy consumption  ...  Our approach aims to search the optimal routing tree which satisfies the minimum scheduling length and energy consumption for wireless sensor networks.  ...  Figure 2 : 2 The length of path and energy consumption. Figure 3 : 3 Graphical interpretation of the weighting method for solving multiobjective problems.  ... 
doi:10.1155/2015/724628 fatcat:4gssdwleinaappwq727cyuinka

Differential evolution for RFID antenna design

James Montgomery, Marcus Randall, Andrew Lewis
2011 Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11  
A common approach taken with permutation problems is to order vector components by their value, thereby producing a permutation of the components.  ...  The operation of the algorithm in a single-objective setting is described first, followed by a survey of adaptations to multiobjective problems in Section 3.2 and subsequently details of its adaptation  ... 
doi:10.1145/2001576.2001669 dblp:conf/gecco/MontgomeryRL11 fatcat:3b7tdfmfivhlbnurgg2tefxp7a

Multiobjective Time Series Matching for Audio Classification and Retrieval

Philippe Esling, Carlos Agon
2013 IEEE Transactions on Audio, Speech, and Language Processing  
We show how this problem can be cast into a new approach merging multiobjective optimization and time series matching, called MultiObjective Time Series (MOTS) matching.  ...  To demonstrate the performances of our approach, we show its efficiency in audio classification tasks.  ...  Edit-based distances like the Longest Common Sub-Sequence (LCSS) [18] handle outliers by allowing gaps in the series.  ... 
doi:10.1109/tasl.2013.2265086 fatcat:rsfwp7fnwjduro2y3jlhqo6bpq

Immune-Endocrine System Inspired Hierarchical Coevolutionary Multiobjective Optimization Algorithm for IoT Service

Zhen Yang, Yongsheng Ding, Yaochu Jin, Kuangrong Hao
2018 IEEE Transactions on Cybernetics  
In IE-HCMOA, a multiobjective immune algorithm based on global ranking with vaccine (GRVIA) is designed to choose superior antibodies.  ...  And we use human forgetting memory mechanism to design two levels memory storage for the choice problem of solutions to achieve promising performance.  ...  So it is going to be a challenging multiobjective optimization problem. Many researchers have attempted to solve the problems of multiobjective service selection in Web service. Trummer et al.  ... 
doi:10.1109/tcyb.2018.2866527 pmid:30235158 fatcat:fvkdvp2xnjc77achdudgi4gzya

Multiobjective Simulation-Based Optimization Based on Artificial Immune Systems for a Distribution Center

Chris S. K. Leung, Henry Y. K. Lau
2018 Journal of Optimization  
a simulation model for solving a real-life multiobjective optimization problem.  ...  The results show that the framework is able to solve large scale problems with a large number of parameters, operators, and equipment involved.  ...  Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this paper.  ... 
doi:10.1155/2018/5852469 fatcat:37dchnlhyre4pjtgyglq2pe6eq
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