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Editorial for the special issue on metaheuristics for combinatorial optimization
2017
Journal of Heuristics
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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]
2004
Lecture notes in economics and mathematical systems
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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
2010
Computer Networks
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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
2007
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
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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
2005
IEEE Transactions on Evolutionary Computation
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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
2018
Zenodo
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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
2022
Mobile Information Systems
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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
2019
Forests
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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
2021
Journal of Sensors
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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]
2015
Advances in Intelligent Systems and Computing
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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
2015
Journal of Sensors
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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
2011
Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11
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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
2013
IEEE Transactions on Audio, Speech, and Language Processing
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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
2018
IEEE Transactions on Cybernetics
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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
2018
Journal of Optimization
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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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