Fuzzy multi-objective optimization for optimum allocation in multivariate stratified sampling with quadratic cost and parabolic fuzzy numbers

Gupta, Neha; Bari, Abdul

doi:10.1080/00949655.2017.1332195

Cited by 9 publications

(9 citation statements)

References 20 publications

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“…. KPI indicators refer to the internal operation of the process, the setting of key input parameters of the operation, sampling, calculation, analysis, and output [19]. It is the foundation of enterprise performance management, and it is a quantifiable target management index that can decompose the highest-level goals into specific implementation and execution subtargets and use this to measure performance.…”

Section: Kpi Indicatorsmentioning

confidence: 99%

Enterprise Performance Optimization Management Decision-Making and Coordination Mechanism Based on Multiobjective Optimization

Zou

Bai

2021

Mathematical Problems in Engineering

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Today’s society is a society of the knowledge economy, and the competition of enterprises is the competition of talents. The rapid development of science and technology and the fierce development of market competition have made the importance of performance management increasingly prominent in corporate management. The purpose of performance management is to explore and deal with some of the effects of various factors on employee performance and to tap the potential of employees, improve employee performance, and also bring a qualitative leap to the performance of the organization. The improvement of the employee performance management level has laid a solid foundation for the improvement of the organizational performance management level. However, there are still some difficulties in the implementation of performance management in my country at this stage, and the management effect is not obvious. Therefore, building a scientific, reasonable, and complete multiobjective optimization-based corporate performance optimization management decision-making and coordination mechanism is the primary task of today’s enterprises. This article will give a brief theoretical overview of the combination of system management theory and behavior management theory, MBO target management, and KPI indicators, build a multiobjective optimization model on an effective theoretical basis, and use genetic algorithms to obtain a weak Pareto effective solution that can optimize the enterprise with consideration of performance appraisal indicators. It also builds an agency model and an analysis of employee incentive plans, which clearly shows the relationship between the company and the management and employees, conducts a cross analysis of the needs of the company’s management and employees, and puts forward the best corporate performance considering the needs of employees; among them, the multiobjective optimization of corporate performance increased by 14% under the optimal management decision.

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Section: Kpi Indicatorsmentioning

confidence: 99%

Enterprise Performance Optimization Management Decision-Making and Coordination Mechanism Based on Multiobjective Optimization

Zou

Bai

2021

Mathematical Problems in Engineering

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“…In addition, using different weighting factors does not guarantee finding different optimal Pareto solutions. The biggest disadvantage of this method is that it cannot find all the solutions, and the optimal Pareto front is a non-curve average surface [18,19].…”

Section: Multi-objective Optimization Solution Methodsmentioning

confidence: 99%

Evaluation of regional industrial cluster innovation capability based on particle swarm clustering algorithm and multi-objective optimization

Yan

Meng

Song

2021

Complex Intell. Syst.

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With the progress of the times and the development of science, industrial clusters have been regarded by all countries in the world as one of the important ways to enhance regional competitiveness, and become an inevitable trend of industrial development. The research on the innovation ability of industrial clusters can not only maintain sustainable development of industrial clusters and obtain sustained competitive advantages, but also provide reference for the government's policy formulation of industrial clusters. This paper aims to study the evaluation of regional industrial clusters' innovation capability based on particle swarm clustering and multi-objective optimization. This paper uses the theory of industrial cluster innovation and takes regional industrial system as the empirical research object to establish a regional industrial system capability evaluation system, which is based on the selection of indicators, combined with analytic hierarchy process and factor analysis to evaluate industrial innovation capability. On this basis, the particle swarm clustering theory is used to verify the innovation ability and evaluation index system of industrial clusters, and provide a reference for the evaluation of the innovation ability of industrial clusters. This paper divides the regional cluster innovation capability into four aspects: innovation input capability, environment support capability, self-development capability and innovation output capability, and systematically analyzes the key elements and in the composition of innovation elements and their relationships. It then constructs the evaluation index system of regional cluster innovation capability. At the same time, this paper introduces clustering analysis algorithm and swarm intelligence algorithm into regional innovation evaluation, combines particle swarm optimization algorithm and K-means clustering algorithm, and optimizes particle swarm clustering algorithm by adjusting adaptive parameters and adding fitness variance. The experimental results of this paper show that from the results of the tested innovation potential of the three industrial clusters, industrial cluster F has the strongest innovation ability, with an evaluation coefficient of 0.851, followed by industrial cluster F, which has a value of 0.623. This result is consistent with the actual innovation status of the selected industry. From this point of view, the established particle swarm clustering model for evaluating the innovation capability of regional industrial clusters is reliable and can be used to evaluate the innovation capability of different industrial clusters.

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“…Due to the limited financial situation of such enterprises, they have to be more careful when making decisions and are forced to put the financial effects of decision-making on process change as the main goal. KPIs are related to the internal operation of the process, the setting of key input parameters of the operation, sampling, calculation, analysis, and output (Gupta & Bari, 2017). It is the basis of enterprise performance management and is a quantifiable target management index that can break down top-level objectives into specific implementation and execution sub-objectives and use them to measure performance (Tao & Sijun, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Impacts of Implemented Changes on Business Performance of Slovak Enterprises

Sujová¹,

Simanová²

2023

CEBR

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The paper aims to investigate the relationship between performing changes and business performance represented by the return on equity (ROE) indicator, and to point out the importance of changes and their management in Slovak enterprises. Relevant data from enterprises in the Slovak Republic were obtained through an online research questionnaire. The evaluation of the questionnaire was carried out using the software program STATISTICA 12 CZ -Stat Soft. Inc. ( 2013). Mathematical-statistical methods were used to examine and evaluate the interrelationships and the effects of individual factors in the implementation of changes on business performance. Statistical analysis was performed through PivotTables. Pearson's chi-square test of independence was used to test the significance of the contingency coefficients, and Cramer's contingency coefficient was used for the intensity of dependence between the signs. The results of the research show that the business performance of Slovak enterprises is directly affected by surveyed aspects of implementing changes. Implications for Central European audience:The results of research into the current state of the performance of Slovak enterprises in various industry fields and the determination of its dependence on the areas of change, type of change, impulses for change and indicators assessing the effects of change are the main contribution to the development of scientific knowledge in the field of change management. The synergy of theoretical knowledge and partial research results provides practical implications on how to achieve higher profitability through the successful implementation of changes and monitoring their effects.

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Fuzzy multi-objective optimization for optimum allocation in multivariate stratified sampling with quadratic cost and parabolic fuzzy numbers

Cited by 9 publications

References 20 publications

Enterprise Performance Optimization Management Decision-Making and Coordination Mechanism Based on Multiobjective Optimization

Enterprise Performance Optimization Management Decision-Making and Coordination Mechanism Based on Multiobjective Optimization

Evaluation of regional industrial cluster innovation capability based on particle swarm clustering algorithm and multi-objective optimization

Impacts of Implemented Changes on Business Performance of Slovak Enterprises

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