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Research on the Construction of Teaching System about BIM Series Courses of Engineering Economics and Management Based on Bayesian Network

General engineering economics, replacement analysis of mutually exclusive projects of unequal lives using kelly specific real option criterion.

This paper presents a model to address the uncertainty inherent in replacement problems, whereby a firm must select between mutually exclusive projects of unequal lifespans by applying the Kelly criterion (which is not well known to the engineering economics community) within a binomial lattice option-pricing environment. Assuming that only the interest rate, among many factors, is uncertain, Brown and Davis performed an economic analysis of this problem by employing a real option-pricing method and argued that their model yields results opposite to those yielded by the traditional approach. However, the results yielded by the model proposed herein are consistent with those by the traditional approach, unlike Brown and Davis’s model. The conclusion is that since the investment time horizon is infinite, a firm rationale pertaining to the selection of the best method for the investment problem of such types does not exist.

Fuzzy Logical Algebra and Study of the Effectiveness of Medications for COVID-19

A fuzzy logical algebra has diverse applications in various domains such as engineering, economics, environment, medicine, and so on. However, the existing techniques in algebra do not apply to delta-algebra. Therefore, the purpose of this paper was to investigate new types of cubic soft algebras and study their applications, the representation of cubic soft sets with δ-algebras, and new types of cubic soft algebras, such as cubic soft δ-subalgebra based on the parameter λ (λ-CSδ-SA) and cubic soft δ-subalgebra (CSδ-SA) over η. This study explains why the P-union is not really a soft cubic δ-subalgebra of two soft cubic δ-subalgebras. We also reveal that any R/P-cubic soft subsets of (CSδ-SA) is not necessarily (CSδ-SA). Furthermore, we present the required conditions to prove that the R-union of two members is (CSδ-SA) if each one of them is (CSδ-SA). To illustrate our assumptions, the proposed (CSδ-SA) is applied to study the effectiveness of medications for COVID-19 using the python program.

Facing the complexity of the economy: an opportunity for the new alliance between economics and engineering

AbstractIn Forging a new alliance between economics and engineering, Sergio Mariotti explores the relationship between economics and engineering. The interactions between economics and engineering is a question rather than trivial and Mariotti faces the problem, firstly, from an historical perspective and, secondly, by identifying the paradigms for the economics–engineering nexus. Three paradigms are proposed, i.e., economics for engineering, economics and engineering, economics as engineering. They offer the opportunity to open new vistas on the future of the relationships between economics and engineering, in particular for facing the complexity of the economy.

Design, systems approaches, and the engineering-economics nexus

Engineering, economics, heidegger … and mariotti: a note, robust approach for optimized path selection in monarch butterfly optimization.

Nature Inspired Computing or (NIC) strives to develop new computing technologies by observing how nature can inspired to solve complex problems under various environmental conditions. This has produced unconventional research in new fields such as neural networks, swarm intelligence, evolutionary computing, and artificial immune systems. NIC technology is used in almost every branch of physics, biology, engineering, economics and even management. In this paper, one of the nature-inspired approach namely Monarch Butterfly Optimization (MBO)is used for modifying the chromosome parameter in it. The new conditional path selection criteria are developed for the movement of individual subpopulation along with the amplitude parameter. Ackley function is implemented by using conditional path selection mathematical model and the effect of amplitude parameter with adjusting ratio has been identified. The results show better performance among the conditional path selection criteria in terms of route optimization selection.

In the Path of Vydūnas: Moral Values and Social Engineering as the Tool for the Welfare State Creation

The article analyses the relationship between democracy and technocracy invoking Lithuanian philosopher Vydūnas’ view on the role of moral values playing in the state. Investigating projects directed to the welfare state creation the author asks how much these projects are technocratic in the narrow sense – performing with the help of knowledge of nature sciences, engineering, economics and other, and what role in these projects moral values play. The author distinguishes two types of projects – technocracy in the narrow and in the wide sense. The latter is defined as social engineering based on the interdisciplinary discussion of experts on the questions linked with moral values. The main theses defended are the following: democracy ant technocracy as the methods of governance should not be contrasted; technocracy could not replace democracy which is the system defending freedom of the individual person; moral ideals (freedom, equality, justice, seeking of common good) are the basic guide in the sphere of values for the social engineering directed to the creation of welfare state.

Course Strategy: Executing High-Enrollment Engineering Economics Online

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A special issue of Journal of Risk and Financial Management (ISSN 1911-8074).

Deadline for manuscript submissions: closed (1 July 2023) | Viewed by 10238

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Dear Colleagues,

JRFM is currently accepting submissions to a Special Issue on “Advances in Engineering Economics” covering all areas of engineering economics, broadly defined.

The main objective of this Special Issue is to publish papers dealing with the analysis of industrial and engineering projects, and, in general, capital asset investments. We welcome methodological developments as well as novel applications and case studies in a number of areas, including, but not limited to:

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Given the interdisciplinary nature of engineering economics, we also welcome papers from accounting scholars, finance scholars, operational researchers, financial mathematicians, and researchers lying at the intersection of engineering, management, finance, or accounting, with the understanding that the focus of the paper involves developing and analyzing the economic and financial consequences of investment decisions.

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Engineering Economics

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Data Engineering for Cognitive Economics

Cognitive economics studies imperfect information and decision-making mistakes. A central scientific challenge is that these can’t be identified in standard choice data. Overcoming this challenge calls for data engineering, in which new data forms are introduced to separately identify preferences, beliefs, and other model constructs. I present applications to traditional areas of economic research, such as wealth accumulation, earnings, and consumer spending. I also present less traditional applications to assessment of decision-making skills, and to human-AI interactions. Methods apply both to individual and to collective decisions. I make the case for broader application of data engineering beyond cognitive economics. It allows symbiotic advances in modeling and measurement. It cuts across existing boundaries between disciplines and styles of research.

Previously circulated as “Economic Data Engineering.” Forthcoming Journal of Economic Literature. Deep thanks to Daniel Martin, Stefan Bucher, and Soren Leth-Petersen for helping me conceptualize the broad sweep and fine details of this paper, as well as four anonymous referees, and particularly the editors, Steven Durlauf and David Romer, for helping me narrow focus and sharpen the presentation. I thank also Alona Bach, Ernst Fehr, Danny Goroff, Markus Reinhard, Mike Woodford, and participants in the Sloan-NOMIS Program on the Cognitive Foundations of Economic Behavior for supporting the broader push toward interdisciplinary research. Finally, I thank the Alfred P. Sloan Foundation for Grant G-2023-19660 which supports research on Cognitive Economics at Work. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

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Economic Surveillance using Corporate Text

Working Paper 2024-022A by Tarek Hassan, Stephan Hollander, Aakash Kalyani, Markus Schwedeler, and Laurence van Lent

Full order of authors: Tarek A. Hassan, Stephan Hollander, Aakash Kalyani, Laurence van Lent, Markus Schwedeler, and Ahmed Tahoun. This article applies simple methods from computational linguistics to analyze unstructured corporate texts for economic surveillance. We apply text-as-data approaches to earnings conference call transcripts, patent texts, and job postings to uncover unique insights into how markets and firms respond to economic shocks, such as a nuclear disaster or a geopolitical event---insights that often elude traditional data sources. This method enhances our ability to extract actionable intelligence from textual data, thereby aiding policy-making and strategic corporate decisions. By integrating computational linguistics into the analysis of economic shocks, our study opens new possibilities for real-time economic surveillance and offers a more nuanced understanding of firm-level reactions in volatile economic environments.

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An Adaptive Differential Evolution Algorithm Based on Data Preprocessing Method and a New Mutation Strategy to Solve Dynamic Economic Dispatch Considering Generator Constraints

• Published: 08 September 2024

Cite this article

• Ruxin Zhao   ORCID: orcid.org/0000-0002-6810-2631 1 ,
• Wei Wang 1 ,
• Tingting Zhang 1 ,
• Chang Liu 2 ,
• Lixiang Fu 1 ,
• Jiajie Kang 1 ,
• Hongtan Zhang 1 ,
• Yang Shi 1 &
• Chao Jiang 1  

Differential evolution (DE) algorithm is a classical natural-inspired optimization algorithm which has a good. However, with the deepening of research, some researchers found that the quality of the candidate solution of the population in the differential evolution algorithm is poor and its global search ability is not enough when solving the global optimization problem. Therefore, in order to solve the above problems, we proposed an adaptive differential evolution algorithm based on the data processing method and a new mutation strategy (ADEDPMS). In this paper, the data preprocessing method is implemented by k -means clustering algorithm, which is used to divide the initial population into multiple clusters according to the average value of fitness, and select candidate solutions in each cluster according to different proportions. This method improves the quality of candidate solutions of the population to a certain extent. In addition, in order to solve the problem of insufficient global search ability in differential evolution algorithm, we also proposed a new mutation strategy, which is called “DE/current-to- \({p}_{1}\) best& \({p}_{2}\) best”. This strategy guides the search direction of the differential evolution algorithm by selecting individuals with good fitness, so that its search range is in the most promising candidate solution region, and indirectly increases the population diversity of the algorithm. We also proposed an adaptive parameter control method, which can effectively balance the relationship between the exploration process and the exploitation process to achieve the best performance. In order to verify the effectiveness of the proposed algorithm, the ADEDPMS is compared with five optimization algorithms of the same type in the past three years, which are AAGSA, DFPSO, HGASSO, HHO and VAGWO. In the simulation experiment, 6 benchmark test functions and 4 engineering example problems are used, and the convergence accuracy, convergence speed and stability are fully compared. We used ADEDPMS to solve the dynamic economic dispatch (ED) problem with generator constraints. It is compared with the optimization algorithms used to solve the ED problem in the last three years which are AEFA, AVOA, OOA, SCA and TLBO. The experimental results show that compared with the five latest optimization algorithms proposed in the past three years to solve benchmark functions, engineering example problems and the ED problem, the proposed algorithm has strong competitiveness in each test index.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions.

This work is supported by the National Natural Science Foundation of China (with number 61906164), by the Natural Science Foundation of Jiangsu Province of China (with number BK20190875).

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Ruxin Zhao, Wei Wang, Tingting Zhang, Lixiang Fu, Jiajie Kang, Hongtan Zhang, Yang Shi & Chao Jiang

School of Intelligent Manufacturing, Yangzhou Polytechnic Institute, Yangzhou, 225127, Jiangsu, China

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Ruxin Zhao, Wei Wang and Tingting Zhang wrote the main manuscript text. Chang Liu, Jiajie Kang and Lixiang Fu prepared figures and tables. Hongtan Zhang, Shi Yang and Chao Jiang were responsible for editing. All authors reviewed the manuscript.

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Zhao, R., Wang, W., Zhang, T. et al. An Adaptive Differential Evolution Algorithm Based on Data Preprocessing Method and a New Mutation Strategy to Solve Dynamic Economic Dispatch Considering Generator Constraints. Comput Econ (2024). https://doi.org/10.1007/s10614-024-10705-2

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Published : 08 September 2024

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