March 2025
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2 Reads
Swarm and Evolutionary Computation
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Publications (80)
December 2024
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6 Reads
Journal of Control and Decision
October 2024
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44 Reads
Project portfolio selection is essential for a company to achieve its strategic goals. Due to constraints such as budget and manpower, companies cannot undertake all projects simultaneously and must prioritize those offering the highest value. Projects often interact and progress through various phases, adding complexity to the selection process. To address these challenges, this study introduces a model that accounts for the multi-stage execution of projects, their interactions, and multiple objectives. A novel multi-objective optimization algorithm is developed to solve this problem, along with a refined project selection method designed to offer decision-makers enhanced insights. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach.
October 2024
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7 Reads
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2 Citations
Advanced Engineering Informatics
September 2024
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15 Reads
Based on the project portfolio selection and scheduling problem (PPSS), the development of a systematic and scientific project scheduling plan necessitates comprehensive consideration of individual preferences and multiple realistic constraints, rendering it an NP-hard problem. Simultaneously, accurately and swiftly evaluating the value of projects as a complex entity poses a challenging issue that requires urgent attention. This paper introduces a novel qualitative evaluation-based project value assessment process that significantly reduces the cost and complexity of project value assessment, upon which a preference-based deep reinforcement learning method is presented for computing and solving project subsets and time scheduling plans. This paper first determines the key parameter values of the algorithm through specific examples. Then, using the method of controlling variables, it explores the sensitivity of the algorithm to changes in problem size and dimensionality. Finally, the proposed algorithm is compared with two classical algorithms and two heuristic algorithms across different instances. The experimental results demonstrate that the proposed algorithm exhibits higher effectiveness and accuracy.
September 2024
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4 Reads
August 2024
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2 Reads
June 2024
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1 Read
June 2024
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135 Reads
Journal of Physics Conference Series
In response to the challenge of multiple fault types and complex diagnostic criteria in bearing fault diagnosis, a case reasoning method based on ensemble learning is proposed. The approach utilizes Case-Based Reasoning (CBR) to construct a case library for vibration-based features of rolling bearings and perform fault diagnosis. Moreover, addressing the issue of determining optimal feature weight ratios when retrieving similar cases in traditional case reasoning methods, a Random Forest algorithm combined with Bayesian Optimization is introduced. This integration allows for adaptive retrieval of similar cases, thereby enhancing the diagnostic capability for bearing faults. The effectiveness of this approach is validated through experimental analysis.
June 2024
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12 Reads
Journal of Physics Conference Series
The process of Industry 4.0 is constantly promoted. In order to realize the high-quality connotation development of enterprises, manufacturing enterprises need to carry out information transformation and upgrading. The technology of information flow analysis can consistently assess the worth of the factory, overcome existing technical challenges, and achieve intelligent modernization and enhancement of the system. This study presents a visualization and evaluation of the factory’s layout, production lines, and workstation from three perspectives: macro, meso, and micro. To begin, a value added heat map (VAHM) is created by examining the visualization technique for information value added information (IVA). This analysis aims to assess the extent of information wastage in terms of the factory’s physical space, resources, and staff. Additionally, a method for analyzing the information gain of a production line, which is based on the concept of distributed cognition, is introduced. This method evaluates the production line by integrating the economic principle of information processing (EPIP). Furthermore, when assessing complexity, the volume of information in workstations is measured and enhanced by applying the principle of information processing economy. Ultimately, the method’s validity and feasibility are confirmed by applying it to real-world manufacturing industry scenarios.
Citations (41)
... Humans are able to use and process fuzzy concepts to form sensations, cognition, and thus reasoning and decision-making, and the human brain can store and process fuzzy information and utilize fuzzy knowledge for fuzzy reasoning, which is the unparalleled superiority of the human brain [22]. Zadeh, an American cybernetics expert, first proposed the concept of fuzzy sets and founded the fuzzy set theory [23], and proposed to quantify the knowledge rules of human fuzzy language with IF-Then fuzzy rules in 1973, which laid the foundation for the theory of fuzziness. ...
- Citing Article
June 2024
Information Sciences
... Furthermore, Zheng et al. [26] design a change propagation path that integrates upstream and downstream linkage searches to address the varying subjective and objective impacts of changes on upstream and downstream characteristics. Additionally, Xu et al. propose a multi-layer heterogeneous network-based method for product requirement development, which aims to predict the scope of propagation during the product development process [27,28]. Nevertheless, significant challenges remain in the automation of constructing intricate networks that are predicated on product structures and functional dependencies. ...
- Citing Article
January 2024
Advanced Engineering Informatics
... Furthermore, Zheng et al. [26] design a change propagation path that integrates upstream and downstream linkage searches to address the varying subjective and objective impacts of changes on upstream and downstream characteristics. Additionally, Xu et al. propose a multi-layer heterogeneous network-based method for product requirement development, which aims to predict the scope of propagation during the product development process [27,28]. Nevertheless, significant challenges remain in the automation of constructing intricate networks that are predicated on product structures and functional dependencies. ...
- Citing Article
October 2023
Advanced Engineering Informatics
... This improvement arises because previous studies, when constructing networks from sequential data, typically overlooked relationships beyond pairwise node connections, implicitly assuming a first-order Markov process. This assumption led to the omission of significant higher-order information present in the original data [14]. To address this issue, Rosvall et al. [15] developed a second-order Markov network model to capture dynamic behaviors, which not only revealed actual travel ...
- Citing Article
- Full-text available
July 2023
... Because user requirements exhibit a dynamic iterative trend, the pace of product updates and iterations is accelerated [24]. Therefore, strategically allocating limited resources for the most impactful product improvements plays an important role for SMEs to maintain their market competitiveness [25]. Currently, although some studies have already paid attention to strategies for product design improvement based on online user reviews, they often fell short of addressing the specific needs of SMEs, i.e., comprehensive understanding of user requirements, prioritizing product improvement attributes, and deciding which should be improved immediately. ...
- Citing Article
April 2023
Advanced Engineering Informatics
... Agile methodologies have undoubtedly enriched the development of softwarebased products with new approaches and perspectives [4]. However, while traditional agile lifecycles such as SCRUM have offered notable contributions to the software development industry, they also suffer from certain limitations when it comes to achieving a higher degree of specification in the UX design of a given solution [5]. ...
- Citing Article
- Full-text available
May 2023
... The authors in [36] highlight the effectiveness of hybrid approaches combining, for example, IP and Constraint Programming (CP) to address the highly constrained NRP. In other cases, researchers have proposed hybrid approaches for the NRP, combining MIP with deep neural network-assisted heuristics and recurrent neural networks, outperforming other pieces of research in terms of benchmarks [37,38]. The following sections attempt to categorise similar future trends. ...
- Citing Article
December 2022
Applied Soft Computing
... As an instance, there are popular products [17], [18] where number of customer visits are much higher than other products. It is reasonable to assume these products are going to have a large number of trigger observations, thus more treatment impact. ...
- Citing Conference Paper
August 2022
... [19] utilized the technique of NER with both machine learning and deep learning method to recognize simple software-related entities in software requirement specification (SRS). [20], [21] classifies the application related reviews requirement into given categories with the BERT model for apps performance analysis. The result ...
- Citing Conference Paper
December 2021
... The authors in [36] highlight the effectiveness of hybrid approaches combining, for example, IP and Constraint Programming (CP) to address the highly constrained NRP. In other cases, researchers have proposed hybrid approaches for the NRP, combining MIP with deep neural network-assisted heuristics and recurrent neural networks, outperforming other pieces of research in terms of benchmarks [37,38]. The following sections attempt to categorise similar future trends. ...
- Citing Article
September 2022
Computers & Industrial Engineering