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Multi-objective Optimization Models for Many-to-one Matching Problems

Natsumi Shimada, Natsuki Yamazaki, Yuichi Takano
2020 Journal of Information Processing  
To pursue these conflicting objectives simultaneously, we propose several multi-objective optimization models for many-to-one matching problems.  ...  This paper is concerned with many-to-one matching problems for assigning resident physicians (residents) to hospitals according to their preferences.  ...  Acknowledgments The authors would like to thank anonymous reviewers who gave valuable feedback to our manuscript.  ... 
doi:10.2197/ipsjjip.28.406 fatcat:lvowrsk7vrdcbh3qyay4ztnp4m

Research on Maximum Return Evaluation of Human Resource Allocation Based on Multi-Objective Optimization

Hong Zhu
2020 Intelligent Automation and Soft Computing  
A few studies turn a one-to-many bilateral matching problem into an equivalent one-to-one bilateral matching problem, and then, under stable matching conditions, a multi-objective automatic capture model  ...  On this basis, a bilateral matching multi-objective decision-making model is established with the objective of optimizing three actual indexes of reasonable grouping.  ...  NOTES ON CONTRIBUTORS  ... 
doi:10.32604/iasc.2020.010108 fatcat:dxaebu3v6rgbjha2romlprthm4

Matchmaking Framework for B2B E-Marketplaces

2010 Informatică economică  
In the literature were proposed many approaches for matchmaking. In this paper we present a conceptual framework of matchmaking in B2B e-marketplaces environment.  ...  The demand and supply matching process becomes complex and difficult on last twenty years since the e-marketplaces play an important role in business management.  ...  We consider that our matching problem is a multi-objective combinatorial optimization problem.  ... 
doaj:68afa425c9854933832d9e207a721fa1 fatcat:aweat7fct5gfdlgmijxjrfm2qq

Two-sided Matching Decision under Multi-granularity Uncertain Linguistic Environment

Yue Qi, Yongshan Peng, Bingwen Yu, Yu Hong, Quan Xiao
2015 International Journal of u- and e- Service, Science and Technology  
Based on this, the two-sided matching problem with multi-granularity uncertain linguistic terms is described.  ...  Furthermore, a multi-objective optimization model is developed by using the extended 2-tuple weighted average.  ...  matrixes A L and B L , we consider to construct an optimization model for obtaining the matching alternative considering matching constraints.  ... 
doi:10.14257/ijunesst.2015.8.11.04 fatcat:3sho3bfxfzhmxhnnhi6rurpfgy

An invariant descriptor map for 3D objects matching

Abdallah El Chakik, Abdul Rahman El Sayed, Hassan Alabboud, Amer Bakkach
2020 International Journal of Engineering & Technology  
Finally, the matching problem is modelled as sub-graph isomorphism problem, which is a combinatorial optimization problem to match feature regions while preserving the geometric.  ...  This paper presents an efficient and robust 3D matching method using vertices descriptors de-tection to define feature regions and an optimization approach for regions matching.  ...  We propose to model the matching problem as a combinational optimization problem using maximum relational subgraph matching and simulated annealing meta-heuristic algorithm.  ... 
doi:10.14419/ijet.v9i1.29918 fatcat:3tlh22hjjbeffeatgjeagwogny

Few-shot Segmentation with Optimal Transport Matching and Message Flow [article]

Weide Liu, Chi Zhang, Henghui Ding, Tzu-Yi Hung, Guosheng Lin
2021 arXiv   pre-print
We further address the few-shot segmentation as a multi-task learning problem to alleviate the domain gap issue between different datasets.  ...  In this work, we argue that every support pixel's information is desired to be transferred to all query pixels and propose a Correspondence Matching Network (CMNet) with an Optimal Transport Matching module  ...  For example, as shown in Figure 2 , the bird's head features are connected to the body features. 3) Unmatched parts. Many query features may be unmatched due to the many-to-one matching problem.  ... 
arXiv:2108.08518v1 fatcat:dj3kxl5klzhdvdvz3yu7r42sci

Self-Organizing Relay Selection in UAV Communication Networks: A Matching Game Perspective [article]

Dianxiong Liu, Yuhua Xu, Jinlong Wang, Yitao Xu, Alagan Anpalagan, Qihui Wu, Hai Wang, Liang Shen
2018 arXiv   pre-print
More effective schemes with distributed, fast, robust and scalable features are required to solve the optimizing problem.  ...  After discussing the challenges and requirements, we find that the matching game is suitable to model the complex relay model.  ...  substitutability: In [11] , we studied the problem of relay selection with multinodes using a many-to-one matching model.  ... 
arXiv:1805.09257v1 fatcat:qdhf3qqcvnbhjhfqlrstngza5y

Getting the most out of additional guidance information in deformable image registration by leveraging multi-objective optimization

Tanja Alderliesten, Peter A. N. Bosman, Arjan Bel, Sébastien Ourselin, Martin A. Styner
2015 Medical Imaging 2015: Image Processing  
Hereto, next to objectives related to match quality and amount of deformation, we define a third objective related to guidance information.  ...  Multi-objective optimization eliminates the need to a-priori tune a weighting of objectives in a single optimization function or the strict requirement of fulfilling hard guidance constraints.  ...  algorithms (EAs) are among the state-of-the-art in solving multiobjective optimization problems. 16 To perform multi-objective optimization, we use a model-based EA.  ... 
doi:10.1117/12.2081438 dblp:conf/miip/AlderliestenBB15 fatcat:bfjzcvrwi5fk3gs6rowxuuo2aq

Practical CO2 — WAG Field Operational Designs Using Hybrid Numerical‐Machine‐Learning Approaches

Qian Sun, William Ampomah, Junyu You, Martha Cather, Robert Balch
2021 Energies  
The Southwest Regional Partnership on Carbon Sequestration (SWP) project desires rigorous history-matching and multi-objective optimization processes, which fits the superiorities of the machine-learning  ...  Although the machine-learning proxy models are trained and validated before imposing to solve practical problems, the error margin would essentially introduce uncertainties to the results.  ...  Treatment of Multiple-Objective Optimizations The optimization studies in this work considered more than one objective function, which are called multi-objective optimization problems (MOO).  ... 
doi:10.3390/en14041055 fatcat:2ux5qn4prncwvl3yuiqeb2ooke

Research on the Parameters Optimization of Hydro-mechanical Compound Transmission with MOGA

Zhen ZHU, Ying-feng CAI, Long CHEN, Chang-gao XIA
2018 DEStech Transactions on Engineering and Technology Research  
Multi-Objective Genetic Algorithm(MOGA) based on Pareto optimal principle is used to solve the parameters optimization problem, including the choice of design variables, the determination of optimization  ...  Under the premise of the implementation of optimum control, the coupling optimization considering parameter and control can be used to solve the parameters matching problem of compound transmission system  ...  This work was supported by the China postdoctoral science foundation (2018M632247),National Natural Science Fund (51805222,U1564201,U1764257),National key research and development plan, key equipment for  ... 
doi:10.12783/dtetr/ecar2018/26317 fatcat:bhkmrohydzdydpxbkvt3hnxfim

Multi-Objective Optimization with an Adaptive Resonance Theory-Based Estimation of Distribution Algorithm: A Comparative Study [chapter]

Luis Martí, Jesús García, Antonio Berlanga, José M. Molina
2011 Lecture Notes in Computer Science  
The introduction of learning to the search mechanisms of optimization algorithms has been nominated as one of the viable approaches when dealing with complex optimization problems, in particular with multi-objective  ...  One of the forms of carrying out this hybridization process is by using multi-objective optimization estimation of distribution algorithms (MOEDAs).  ...  multi-objective problems with many objectives.  ... 
doi:10.1007/978-3-642-25566-3_36 fatcat:gyry2bk5ajeormq3kmiqc5a3oy

Multi-objective global optimization for hydrologic models

Patrice Ogou Yapo, Hoshin Vijai Gupta, Soroosh Sorooshian
1998 Journal of Hydrology  
However, practical experience with model calibration suggests that no single-objective function is adequate to measure the ways in which the model fails to match the important characteristics of the observed  ...  selection of an automatic optimization algorithm to search for the parameter values which minimize that distance.  ...  Acknowledgements The authors wish to express their gratitude to the  ... 
doi:10.1016/s0022-1694(97)00107-8 fatcat:tgvci73iivfoll4u4nohzzud4a

Moving away from error-based learning in multi-objective estimation of distribution algorithms

Luis Martí, Jesús García, Antonio Berlanga, José M. Molina
2010 Proceedings of the 12th annual conference on Genetic and evolutionary computation - GECCO '10  
In this work we analyze the model-building issue and the requirements it imposes on the learning paradigm being used.  ...  We experimentally show that thanks to MARTEDA's novel model-building approach and an indicator-based population ranking the algorithm it is able to outperform similar MO-EDAs and MOEAs.  ...  multi-objective problems with many objectives.  ... 
doi:10.1145/1830483.1830585 dblp:conf/gecco/MartiGBM10 fatcat:n2a4ntmwofcihpc6v7553ocbzu

Shared Mobility Problems: A Systematic Review on Types, Variants, Characteristics, and Solution Approaches

Kien Hua Ting, Lai Soon Lee, Stefan Pickl, and Hsin-Vonn Seow
2021 Applied Sciences  
The Shared Mobility Problems (SMP) with the rideshare concept based on sharing a vehicle are fast becoming a trend in many urban cities around the world.  ...  From this systematic review, it is observed that both the time window and multi-objective problems are popular among the researchers, while the minimisation of the total cost is the main concern in the  ...  Thus, in [85] two heuristics based on SA and TS are presented to solve the network-based carpool matching model for a 3+ person home-to-work carpooling problem. Many-to-One Carpooling Problem Ref.  ... 
doi:10.3390/app11177996 fatcat:wxk3fns3lbhydlx7vmr6on5doi

Intelligent computing and applications (LSMS and ICSEE 2010)

Kang Li, Haibo He, Qun Niu
2012 Neural computing & applications (Print)  
Many real-world problems can be formulated as optimization problems, but they are complex and NP hard, and conventional optimization approaches often fail to perform well.  ...  Due to the complexity of stochastic inventory optimization in a multi-echelon system, few analytical models and effective algorithms exist.  ...  Many real-world problems can be formulated as optimization problems, but they are complex and NP hard, and conventional optimization approaches often fail to perform well.  ... 
doi:10.1007/s00521-012-1122-z fatcat:ckg2p5kt3bethmmv3trx7bqbki
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