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A Cost-Minimizing Algorithm for School Choice
[article]
2013
arXiv
pre-print
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The school choice problem concerns the design and implementation of matching mechanisms that produce school assignments for students within a given public school district. ...
We then use this criterion to adapt a well-known combinatorial optimization technique (Hungarian algorithm) to the school choice problem. ...
Our preference index naturally associates a "cost" to each matching and as a result we conceptualize the school choice problem as a "cost minimizing" assignment problem. ...
arXiv:1010.2312v2
fatcat:ij7qtzsjmzafxpgm6bf6o2d34y
School Choice as a One-Sided Matching Problem: Cardinal Utilities and Optimization
[article]
2013
arXiv
pre-print
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The school choice problem concerns the design and implementation of matching mechanisms that produce school assignments for students within a given public school district. ...
We adapt a well-known combinatorial optimization technique (the Hungarian algorithm) as the kernel of this class of matching mechanisms. ...
This paper evolved from work the authors presented in a special paper session on computational social choice at a conference (ISAIM 2012 (International Symposium on Artificial Intelligence and Mathematics ...
arXiv:1304.7413v2
fatcat:pwy5fbwj45cgpeyhap4oikjh7y
Page 1323 of Psychological Abstracts Vol. 54, Issue 5
[page]
1975
Psychological Abstracts
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A list of 12 types of learning algorithms and the class of learning objectives each supports, separate tables for choosing instructional delivery systems for each algorithm, and a cost model for comparing ...
—Describes a technique for choosing cost-
effective instructional delivery systems for proposed
training programs—the Training Effectiveness, Cost Effectiveness Prediction (TECEP) technique. ...
A Fast Efficient Local Search-Based Algorithm for Multi-Objective Supply Chain Configuration Problem
2020
IEEE Access
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This paper focuses on a multi-objective SCC (MOSCC) problem for minimizing both the cost of goods sold and the lead time simultaneously. ...
Firstly, instead of use of population, two solutions (x A and x B ) are generated by the greedy strategy, which have the minimal cost and the minimal time, respectively. ...
Firstly, for a node, the base choice is randomly chosen from the choices whose cost and time are both larger than zero. ...
doi:10.1109/access.2020.2983473
fatcat:hvopd5bahfeyrf33e5sxjigcly
Supervisor-Worker Problems with an Application in Education
2021
Sensors
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The worker plans to achieve his/her own goals (completing an e-learning session) at a minimal cost (effort required to solve problems). ...
We deploy SWOPP for the first time in a real-world study to personalize math questions for K5 students using an e-learning software in schools. ...
Both algorithms output a revised cost function for the worker that produces an optimal plan for the worker (minimizes its costs) while fulfilling the goals for both supervisor and worker. ...
doi:10.3390/s21061965
pmid:33799616
pmcid:PMC8000913
fatcat:6v42dkc7z5dthgtzpnhpkempmm
Can School Enrolment and Performance be Improved by Maximizing Students' Sense of Choice in Elective Subjects?
2020
Journal of Learning Analytics
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This paper explores a system that attempts to maximize high school students' sense of choice when selecting elective subjects. ...
We analyze the underlying computational problem encountered in this task and describe a suitable AI-based optimization algorithm that we have made available for free download. ...
Acknowledgements The authors would like to thank Dave Roberts from Cathedral School, Cardiff, for useful discussions on producing options columns. ...
doi:10.18608/jla.2020.71.6
fatcat:7kpkvqaxkncwxp4xuwfp4xpjsm
Optimization-based learning with bounded error for feedforward neural networks
2002
IEEE Transactions on Neural Networks
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An optimization-based learning algorithm for feedforward neural networks is presented, in which the network weights are determined by minimizing a sliding-window cost. ...
The algorithm is particularly well suited for batch learning and allows one to deal with large data sets in a computationally efficient way. ...
ACKNOWLEDGMENT The authors are grateful to the anonymous reviewers for their constructive comments. ...
doi:10.1109/72.991413
pmid:18244429
fatcat:mfzg3hbwdvdflh4v6hhixu6awm
Development of a Modified Simulated Annealing to School Timetabling Problem
2015
International Journal of Applied Information Systems
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The developed MSA algorithm produced feasible high school timetables at the most reasonable computational cost of 11.59 for JSS and 22.79 for SSS. ...
Others, referred as soft constraints, reflect the preferences given by the teachers or by the policies of the school (for example, teachers want to minimize the holes in their schedule, and a school policy ...
doi:10.5120/ijais14-451277
fatcat:rqwgeegtlzekhekr23k4brpkdy
Reducing the role of random numbers in matching algorithms for school admission
[article]
2016
arXiv
pre-print
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New methods for solving the college admissions problem with indifference are presented and characterised with a Monte Carlo simulation in a variety of simple scenarios. ...
Based on a qualifier defined as the average rank, it is found that these methods are more efficient than the Boston and Deferred Acceptance algorithms. ...
A value of 10 means that a school is ten times more likely to appear as a first choice than a school with a value of 1. ...
arXiv:1609.08394v1
fatcat:2cma7ls3ajgztk2t35tjiaiv5y
ESTIMATION OF DYNAMIC DISCRETE CHOICE MODELS BY MAXIMUM LIKELIHOOD AND THE SIMULATED METHOD OF MOMENTS
2015
International Economic Review
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and for assisting in the study of accuracy bounds for the computational algorithm. ...
SMM) estimation for dynamic discrete choice models. ...
For high school graduation, even the average cost is negative. Psychic costs play a dominant role in explaining schooling decisions. ...
doi:10.1111/iere.12107
pmid:26494926
pmcid:PMC4610014
fatcat:z3mgcwczsjcvbhsjg5yt5scpyy
Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments
2014
Social Science Research Network
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and for assisting in the study of accuracy bounds for the computational algorithm. ...
SMM) estimation for dynamic discrete choice models. ...
For high school graduation, even the average cost is negative. Psychic costs play a dominant role in explaining schooling decisions. ...
doi:10.2139/ssrn.2518370
fatcat:o2shw2nrhnf57p5kbq3f6ddxem
Optimizing Locations of Primary Schools in Rural Areas of China
2021
Complexity
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The object of this study is to minimize the total transportation costs for students, construction costs for new schools, and the construction and upgrading costs for roads on a traffic network with travel ...
A mixed-integer programming model for this problem was proposed. Furthermore, a hybrid simulated annealing algorithm was used to solve the problem. ...
costs (including the travel costs for students, construction costs for school facilities, and the construction and upgrading costs for roads) are minimized. ...
doi:10.1155/2021/7573700
fatcat:d3bf7zt5kncvbicfaqx4vbliua
An Efficient Mechanism for Computation Offloading in Mobile-Edge Computing
[article]
2020
arXiv
pre-print
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In particular, an assignment mechanism called school choice is employed to assist heterogeneous users to select different MEC operators in a distributed environment. ...
The present research has designed an efficient mechanism for a computation offloading scheme that achieves minimal price and energy consumption under latency constraints. ...
Several approaches can solve the school choice problem, including the Deferred Acceptance Algorithm (DA) and the Immediate Acceptance Algorithm (IA). ...
arXiv:1909.06849v2
fatcat:k6pce72u7jg5hp3w6zcmsma74q
Materialized Cube Selection Using Particle Swarm Optimization Algorithm
2016
Procedia Computer Science
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by minimizing query processing cost. ...
Storage of pre-computed views in data warehouse can essentially reduce query processing cost for decision support queries. The problem is to choose an optimal set of materialized views. ...
Our objective is select a set of cubes M to minimize the following cost function (equation 4) for executing the queries under the space constraint
Fig. 2 . 2 Result comparison for GA and PSO algorithm ...
doi:10.1016/j.procs.2016.03.002
fatcat:ogshblqftnbwdmmqliztfxppji
Optimizing schools' start time and bus routes
2019
Proceedings of the National Academy of Sciences of the United States of America
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We present an optimization model for the school time selection problem (STSP), which relies on a school bus routing algorithm that we call biobjective routing decomposition (BiRD). ...
Maintaining a fleet of buses to transport students to school is a major expense for school districts. ...
The Julia language and its JuMP extension for optimization significantly eased the implementation of our algorithms. We thank the editor and reviewers for many helpful suggestions. ...
doi:10.1073/pnas.1811462116
fatcat:5eaiz3ry45gwfars5ln67pnoay
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