scholarly journals Clustering problems in optimization models

1996 ◽  
Vol 9 (3) ◽  
pp. 229-239 ◽  
Author(s):  
Santosh Kabadi ◽  
Katta G. Murty ◽  
Cosimo Spera
Keyword(s):  
Optimization Models ◽  
Clustering Problems

Modeling And Optimization Of The Construction Organization's Production Program

2020 ◽  
pp. 49-56
Keyword(s):  
Software Package ◽  
Target Function ◽  
Optimization Models ◽  
Labor Resource ◽  
Production Program ◽  
Construction Organizations ◽  
Source Data ◽  
Labor Resources ◽  
Construction Organization ◽  
Planning Production

In the article, the author considers the problems of complex algorithmization and systematization of approaches to optimizing the work plans of construction organizations (calendar plans) using various modern tools, including, for example, evolutionary algorithms for "conscious" enumeration of options for solving a target function from an array of possible constraints for a given nomenclature. Various typical schemes for modeling the processes of distribution of labor resources between objects of the production program are given, taking into account the array of source data. This data includes the possibility of using the material and technical supply base (delivery, storage, packaging) as a temporary container for placing the labor resource in case of released capacity, quantitative and qualification composition of the initial labor resource, the properties of the construction organization as a counterparty in the contract system with the customer of construction and installation works etc. A conceptual algorithm is formed that is the basis of the software package for operational harmonization of the production program ( work plans) in accordance with the loading of production units, the released capacities of labor resources and other conditions stipulated by the model. The application of the proposed algorithm is most convenient for a set of objects, which determines the relevance of its implementation in optimization models when planning production programs of building organizations that contain several objects distributed over a time scale.

Combinatorial Optimization of Clustering Decisions: An Application to Refine Psychiatric Diagnoses

2018 ◽  
Author(s):  
Jordan Stevens ◽  
Douglas Steinley ◽  
Cassandra L. Boness ◽  
Timothy J Trull ◽  
...  
Keyword(s):  
Combinatorial Optimization ◽  
Alcohol Use Disorder ◽  
Point Of View ◽  
Psychiatric Diagnoses ◽  
Optimal Solutions ◽  
Specific Function ◽  
Significant Information ◽  
Diagnosis Group ◽  
Clustering Problems ◽  
Unique Application

Using complete enumeration (e.g., generating all possible subsets of item combinations) to evaluate clustering problems has the benefit of locating globally optimal solutions automatically without the concern of sampling variability. The proposed method is meant to combine clustering variables in such a way as to create groups that are maximally different on a theoretically sound derivation variable(s). After the population of all unique sets is permuted, optimization on some predefined, user-specific function can occur. We apply this technique to optimizing the diagnosis of Alcohol Use Disorder. This is a unique application, from a clustering point of view, in that the decision rule for clustering observations into the diagnosis group relies on both the set of items being considered and a predefined threshold on the number of items required to be endorsed for the diagnosis to occur. In optimizing diagnostic rules, criteria set sizes can be reduced without a loss of significant information when compared to current and proposed, alternative, diagnostic schemes.

COMPARISON OF TWO OPTIMIZATION MODELS FOR CONSTRUCTING PATTERNS IN THE METHOD OF LOGICAL ANALYSIS OF DATA

2020 ◽  
pp. 10-13
Author(s):  
Р.И. Кузьмич ◽  
А.А. Ступина ◽  
С.Н. Ежеманская ◽  
А.П. Шугалей
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Logical Analysis ◽  
Optimization Models ◽  
Logical Analysis Of Data

Предлагаются две оптимизационные модели для построения информативных закономерностей. Приводится эмпирическое подтверждение целесообразности использования критерия бустинга в качестве целевой функции оптимизационной модели для получения информативных закономерностей. Информативность, закономерность, критерий бустинга, оптимизационная модель Comparison of two optimization models for constructing patterns in the method of logical analysis of data Two optimization models for constructing informative patterns are proposed. An empirical confirmation of the expediency of using the boosting criterion as an objective function of the optimization model for obtaining informative patterns is given.

scholarly journals A comparison of optimization models for lumber production planning

2015 ◽  
Vol 36 (2) ◽  
pp. 239-246 ◽  
Author(s):  
Francisco P Vergara ◽  
Cristian D Palma ◽  
Héctor Sepúlveda
Keyword(s):  
Production Planning ◽  
Optimization Models

Relaxed optimization models for spectrum auctions

2020 ◽  
Author(s):  
Carlos Agualimpia-Arriaga ◽  
Carlos Adrian Correa-Florez ◽  
Carlos Ivan Paez Rueda
Keyword(s):  
Optimization Models ◽  
Spectrum Auctions

Dual hesitant fuzzy decision making in optimization models

2021 ◽  
Vol 154 ◽  
pp. 107103
Author(s):  
Fanyong Meng ◽  
Jie Tang ◽  
Witold Pedrycz
Keyword(s):  
Decision Making ◽  
Optimization Models ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision

scholarly journals Linear-time approximation schemes for clustering problems in any dimensions

2010 ◽  
Vol 57 (2) ◽  
pp. 1-32 ◽  
Author(s):  
Amit Kumar ◽  
Yogish Sabharwal ◽  
Sandeep Sen
Keyword(s):  
Linear Time ◽  
Approximation Schemes ◽  
Time Approximation ◽  
Clustering Problems

scholarly journals Optimization models for computer data storage design: An application

1994 ◽  
Vol 26 (4) ◽  
pp. 743-756
Author(s):  
Marco Gagliardi ◽  
Cosimo Spera
Keyword(s):  
Data Storage ◽  
Optimization Models ◽  
Computer Data
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