Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity

Pascual, Aitor Iriondo; Smedberg, Henrik; Högberg, Dan; Syberfeldt, Anna; Lämkull, Dan

doi:10.3390/su14094894

Cited by 6 publications

(4 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…On the contrary, Ref. [28] focused on the social aspect, using the multi-objective function for optimizing productivity and worker well-being, but no other aspects were taken into account.…”

Section: Discussionmentioning

confidence: 99%

Multi-Objective Optimization of the Organization’s Performance for Sustainable Development

Fechete

Nedelcu

2022

Sustainability

View full text Add to dashboard Cite

Sustainable development can be defined in terms of three main components: ecologically sustainable, economically sustainable, and socially sustainable. Conflicting objectives are involved in sustainable development issues, of which the economic, environmental, and social objectives are the most important. Multi-criteria decision-making provides a systematic methodology that combines these conflicting objectives and can provide a rational compromise solution to complex decision-making issues. Using multi-objective optimization, this paper integrated three major objectives of organizational performance, maximizing sales, minimizing expenses, and maximizing productivity, all of which are combined for the sustainable development of the organization. All these conflicting problems were included in an objective function that allowed for solving the three objectives simultaneously and, thus, achieving economic, environmental, and social performance, in order to sustainably develop the organization. The input data included the objectives planned by the company regarding the turnover to be achieved, the production and delivery costs, and the productivity achieved by employees. Customer orders, production capacity, delivery costs, and resource consumption were also taken into account for optimization. With the help of multi-objective linear programming, the optimal number of parts produced and delivered by the company was determined so as to reach its economic, environmental, and social performance.

show abstract

Section: Discussionmentioning

confidence: 99%

Multi-Objective Optimization of the Organization’s Performance for Sustainable Development

Fechete

Nedelcu

2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…The simplified formula can improve the calculation speed. 3 Similarity Based on Transformation of Ordinal Variables Ordinal variables refer to categorical variables with ordinal meaning, which can usually be sorted according to a specific order meaning. In the Knowledge Element, the sentiment orientation of the topic can be classified as an ordinal variable.…”

Section: Generating Knowledge Solutions Based On the Knowledge Elemen...mentioning

confidence: 99%

“…In this paper, social media specifically refers to professional social media, which is defined as an online content production platform used by internet users to share and exchange opinions, insights, experiences, and creative ideas related to a specific professional subject, containing a large text corpus with valuable information in the form of comments and articles published by users [1]. Users and enterprises also realized that the information needed to support their decision making is not isolated or fragmented information but rather is specified and interrelated knowledge [2,3]. However, professional social media text is characterized by a large volume, varying lengths, strong professional relevance, a high level of creativity, and the use of colloquial language.…”

Section: Introductionmentioning

confidence: 99%

A Social Media Knowledge Retrieval Method Based on Knowledge Demands and Knowledge Supplies

2023

View full text Add to dashboard Cite

In large social media knowledge retrieval systems, employing a keyword-based fuzzy matching method to obtain knowledge presents several challenges, such as irrelevant, inaccurate, disorganized, or non-systematic knowledge results. Therefore, this paper proposes a knowledge retrieval method capable of returning hierarchical, systematized knowledge results. The method can match the knowledge demands according to the keyword input by users and then present the knowledge supplies corresponding to the knowledge demands as results to the users. Firstly, a knowledge structure named Knowledge Demand is designed to represent the genuine needs of social media users. This knowledge structure measures the popularity of topic combinations in the Topic Map, so the topic combinations with high popularity are regarded as the main content of the Knowledge Demands. Secondly, the proposed method designs a hierarchical and systematic knowledge structure, named Knowledge Supply, which provides Knowledge Solutions matched with the Knowledge Demands. The Knowledge Supply is generated based on the Knowledge Element Repository, using the BLEU similarity matrix to retrieve Knowledge Elements with high similarity, and then clustering these Knowledge Elements into several knowledge schemes to extract the Knowledge Solutions. The organized Knowledge Elements and Knowledge Solutions are the presentation of each Knowledge Supply. Finally, this research crawls posts in the “Autohome Forum” and conducts an experiment by simulating the user’s actual knowledge search process. The experiment shows that the proposed method is an effective knowledge retrieval method, which can provide users with hierarchical and systematized knowledge.

show abstract

“…Algoritma yang digunakan pada penelitian ini adalah algoritma apriori dan algoritma Fp-Growth. Dalam mencari suatu pola kombinasi item yang dapat memenuhi syarat minimum dari nilai support dalam basis data (Hasugian, 2017;Iriondo Pascual et al, 2022) . Setelah menemukan semua sampel dengan frekuensi tinggi maka selanjutnya akan mencari aturan asosiasi yang dapat menemukan suatu pola yang memenuhi persyaratan minimum dengan menghitung jumlah aturan asosiasi A → B (Saefudin et al, 2019).…”

Section: Metodeunclassified

Implementasi Algoritma Apriori dan FP-Growth pada Penjualan Spareparts

Wadanur

Sari

2022

Edumatic

View full text Add to dashboard Cite

Data Mining can be applied in various areas, for example in PT. Agung Toyota Denpasar in order to increase sales and determine the sale of replacement parts. The current problem is to determine the replacement parts sale in PT. Agung Toyota Denpasar cannot know the purchasing habits of customers or customers in purchasing replacement parts purchased simultaneously. This research aims to implement apriori algorithms and fp-growth algorithms to form a model or a combination of rules so that businesses can increase their sales. Using the Knowledge Discovery Database (KDD) method should provide significant information on transaction patterns purchased simultaneously using the apriori and fp-growth algorithms. The dataset used to support this research is the sales transactional dataset for the period of January 2022. The results showed that the 10 best association rules of apriori algorithms and fp-growth algorithms were ready to be used to increase sales with a minimum support value of 85%, confidence value of 100%, and the highest lift ratio of 2.03.

show abstract

Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity

Cited by 6 publications

References 33 publications

Multi-Objective Optimization of the Organization’s Performance for Sustainable Development

Multi-Objective Optimization of the Organization’s Performance for Sustainable Development

A Social Media Knowledge Retrieval Method Based on Knowledge Demands and Knowledge Supplies

Implementasi Algoritma Apriori dan FP-Growth pada Penjualan Spareparts

Contact Info

Product

Resources

About