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.

Logical Analysis of Data-A Survey Paper

2017 ◽  
Vol 7 (3) ◽  
pp. 227-229
Author(s):  
Himani Chauhan ◽  
◽  
Garima Saxena ◽  
Arpit Tripathi ◽  
◽  
...  
Keyword(s):  
Logical Analysis ◽  
Logical Analysis Of Data ◽  
Survey Paper

Research on the Properties of Coaxality Error Objective Function

2009 ◽  
Vol 16-19 ◽  
pp. 1164-1168 ◽  
Author(s):  
Ping Liu ◽  
San Yang Liu
Keyword(s):  
Euclidean Space ◽  
Objective Function ◽  
Optimization Model ◽  
Dimensional Euclidean Space ◽  
Modern Theory ◽  
Minimal Point ◽  
Zone Method ◽  
Deviation Measurement ◽  
Minimum Zone ◽  
Theoretical Results

The unconstrained optimization model applying to radial deviation measurement is established for assessing coaxality errors by the positioned minimum zone method. The properties of the objective function in the optimization model are thoroughly researched. On the basis of the modern theory of convex functions, it is strictly proved that the objective function is a continuous and non-differentiable and convex function defined on the four-dimensional Euclidean space R4. Therefore, the global minimal value of the objective function is unique and any of its minimal point must be its global minimal point. Thus, any existing optimization algorithm, as long as it is convergent, can be used to solve the objective function to get the wanted values of coaxality errors by the positioned minimum zone assessment. An example is given to verify the theoretical results presented.

Optimal fuzzy scheduling and sequencing of multiple-period operating room

2017 ◽  
Vol 32 (1) ◽  
pp. 108-121 ◽  
Author(s):  
Abbas Al-Refaie ◽  
Mays Judeh ◽  
Ming-Hsien Li
Keyword(s):  
Optimization Model ◽  
Real Life ◽  
Operating Rooms ◽  
Decision Makers ◽  
Operating Costs ◽  
Optimization Models ◽  
Patients Satisfaction ◽  
Fuzzy Scheduling ◽  
Sequencing Problems

AbstractLittle research has considered fuzzy scheduling and sequencing problem in operating rooms. Multiple-period fuzzy scheduling and sequencing of patients in operating rooms optimization models are proposed in this research taking into consideration patient‘s preference. The objective of the scheduling optimization model is obtaining minimal undertime and overtime and maximum patients' satisfaction about the assigned date. The objective of sequencing the optimization model is both to minimize overtime and to maximize patients' satisfaction about the assigned time. A real-life case study from a hospital that offers comprehensive surgical procedures for all surgical specialties is considered for illustration. Research results showed that the proposed models efficiently scheduled and sequenced patients while considering their preferences and hospitals operating costs. In conclusion, the proposed optimization models may result in improving patient satisfaction, utilizing hospital's resources efficiently, and providing assistance to decision makers and planners in solving effectively fuzzy scheduling and sequencing problems of operating rooms.

scholarly journals The optimization model of the logging machinery usage in forestry practice

2009 ◽  
Vol 57 (6) ◽  
pp. 105-112 ◽  
Author(s):  
Jitka Janová ◽  
M. Lindnerová
Keyword(s):  
Decision Making ◽  
Czech Republic ◽  
Decision Support ◽  
Decision Support Systems ◽  
Optimization Model ◽  
Support Systems ◽  
Decision Problems ◽  
Optimization Models ◽  
Ongoing Research ◽  
The Impact

The decision support systems commonly used in industry and economy managerial practice for optimizing the processes are based on algoritmization of the typical decision problems. In Czech forestry business, there is a lack of developed decision support systems, which could be easily used in daily practice. This stems from the fact, that the application of optimization methods is less successful in forestry decision making than in industry or economy due to inherent complexity of the forestry decision problems. There is worldwide ongoing research on optimization models applicable in forestry decision making, but the results are not globally applicable and moreover the cost of possibly arising software tools are indispensable. Especially small and medium forestry companies in Czech Republic can not afford such additional costs, although the results of optimization could positively in­fluen­ce not only the business itself but also the impact of forestry business on the environment. Hence there is a need for user friendly optimization models for forestry decision making in the area of Czech Republic, which could be easily solved in commonly available software, and whose results would be both, realistic and easily applicable in the daily decision making.The aim of this paper is to develop the optimization model for the machinery use planning in Czech logging firm in such a way, that the results can be obtained using MS EXCEL. The goal is to identify the integer number of particular machines which should be outsourced for the next period, when the total cost minimization is required. The linear programming model is designed covering the typical restrictions on available machinery and total volume of trees to be cut and transported. The model offers additional result in the form of optimal employment of particular machines. The solution procedure is described in detail and the results obtained are discussed with respect to its applicability in practical forestry decision making. The possibility of extension of suggested model by including additional requirements is mentioned and the example for the wood manipulation requirement is shown.

scholarly journals A decomposability index in logical analysis of data

2004 ◽  
Vol 142 (1-3) ◽  
pp. 165-180 ◽  
Author(s):  
Hirotaka Ono ◽  
Mutsunori Yagiura ◽  
Toshihide Ibaraki
Keyword(s):  
Logical Analysis ◽  
Logical Analysis Of Data

A multi-objective optimization model for logistic planning in the crisis response phase

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Mahdi Ershadi ◽  
Hossein Shams Shemirani
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Crisis Response ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Proposed Model ◽  
Different Types ◽  
Response Phase ◽  
Logistic Planning

PurposeProper planning for the response phase of humanitarian relief can significantly prevent many financial and human losses. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of injured people, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified injured people.Design/methodology/approachThe main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized injured people in the network. Besides, the total transportation activities of different types of vehicles are considered as another objective function. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize transportation activities as the second objective function while maintaining the optimality of the first objective function.FindingsThe performances of the proposed model were analyzed in different cases and its robust approach for different problems was shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.Practical implicationsThe proposed methodology can be applied to find the best response plan for all crises.Originality/valueIn this paper, we have tried to use a multi-objective optimization model to guide and correct response programs to deal with the occurred crisis. This is important because it can help emergency managers to improve their plans.

REDUCTION OF THE CLASSIFIER IN THE METHOD OF LOGICAL ANALYSIS OF DATA BASED ON THE Ε-, Δ-CRITERION FOR SELECTING PATTERN

2021 ◽  
pp. 4-8
Author(s):  
Р.И. Кузьмич ◽  
А.А. Ступина ◽  
В.А. Соколов ◽  
И.С. Поважнюк
Keyword(s):  
Training Sample ◽  
Logical Analysis ◽  
Logical Analysis Of Data ◽  
Sample Application ◽  
Subsequent Selection ◽  
Selection Of ◽  
Algorithmic Procedure

Предлагается алгоритмическая процедура редукции классификатора в методе логического анализа данных, основанная на отборе закономерностей с помощью ε-, δ-критерия. Реализация подхода заключается в формировании исходного классификатора как набора закономерностей на базе наблюдений обучающей выборки, применения к полученным правилам процедуры наращивания и последующего их отбора в новый классификатор на базе ε-, δ-критерия. Приводится эмпирическое подтверждение целесообразности данной алгоритмической процедуры. An algorithmic procedure for the reduction of the classifier in the method of logical analysis of data, based on the selection of patterns using the ε-, δ-criterion is proposed. The implementation of the approach consists in the formation of the initial classifier as a set of patterns based on observations of the training sample, application of the increasing procedure to the obtained patterns and their subsequent selection into a new classifier based on the ε-, δ-criterion. An empirical confirmation of the expediency of this algorithmic procedure is given.

Sign in / Sign up

Export Citation Format

Share Document