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Advanced Soft Computing for Smart Practices of Circular Economy in the Era of Covid-19

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Economic and Business Aspects of Sustainability".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 12950

Special Issue Editors

Dr. Dragan Pamucar

grade E-Mail Website
Assistant Guest Editor
Department of logistics, University of Defence, Belgrade, Pavla Jurišića Šturma 33, 11000 Belgrade, Serbia
Interests: multi-criteria decision making problems; computational intelligence; sustainability neuro-fuzzy systems; fuzzy; rough and intuitionistic fuzzy set theory; neutrosophic theory
Special Issues, Collections and Topics in MDPI journals
Dr. Abbas Mardani

E-Mail Website
Assistant Guest Editor
Department of Marketing, Muma College of Business, University of South Florida, Tampa, FL 33813, USA
Interests: machine learning; sustainable development; entropy; decision making methods; operation management; sustainability
Special Issues, Collections and Topics in MDPI journals
Dr. Jingzheng Ren

E-Mail Website
Assistant Guest Editor
1. Department of Technology and Innovation, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
2. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: process system engineering; sustainability engineering; engineering operations management; artificial intelligence; process simulation, integration and optimization; multi-criteria decision analysis
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Fausto Cavallaro

E-Mail Website
Chief Guest Editor
Department of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy
Interests: multi-criteria; fuzzy set; soft computing; renewable energy; sustainability; circular economy; technology assessment; hypersoft sets; sustainable development goals
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

 The 2030 Agenda for Sustainable Development of the United Nations and the Paris Agreement on climate change, both adopted in 2015, represent two fundamental contributions to guide the transition towards an economic development model that has as its objective not only in profitability but also social progress and environmental protection. In this context, a crucial aspect is the more rational and sustainable management of natural resources, reducing the pollution and pressure due to the increase the demand for natural raw materials. This is a problem related to managing resources more efficiently while reducing waste, keeping as much as possible the value of products and materials. It is necessary to avoid the fact that everything that still intrinsically has a residual utility is not disposed in landfills but is recovered and reintroduced into the production cycles. These aspects constitute the essence of the circular economy, which aims through innovation technology and sustainable management to make economic activities more efficient and less impactful on the environment. Circularity is an essential part of a wider transformation of industry towards climate neutrality and long-term competitiveness. It can generate extra value and unlock economic opportunities.

The transition to a circular economy requires a coherent system of regulatory and economic tools and the involvement of all components of all stakeholders of the social system (enterprises, consumers/citizens, local authorities and NGOs). The EU launched the European Green Deal, a concerted strategy for a climate-neutral, resource-efficient and competitive economy. The European Green Deal provides an action plan to boost the efficient use of resources by moving to a clean and circular economy. The plan outlines the investments needed, and explains how to ensure an inclusive transition.

The health crisis caused by COVID-19 has had terrible consequences on the economy of almost every country in the world and, during the period of the pandemic, environmental emergencies have, of course, lost priority. Recently, EU leaders agreed on a comprehensive package that combines the multiannual financial framework (MFF) and an extraordinary recovery effort, Next Generation EU (NGEU). The package will help the EU to rebuild after the COVID-19 pandemic and will support investments in the Green Deal and sustainable development.

To increase the effectiveness of the transition to a circular economy, new tools based on soft computing can play an important role in the decision processes. Because of the vagueness and uncertainty of the available information, in many situations, decision makers often show a certain degree of hesitation in their decision-making processes. Soft computing can deal with this ambiguity and partial truth. Thus, it represents a valid tool to supply reasonable solutions to real life complex problems.

This Special Issue welcomes papers contributing to novel applications of soft computing for a better understanding of the relationship between the circular economy, uncertainty and vagueness. Relevant topics include, but are not limited, to current research about applications for sustainable development, sustainability evaluation, sustainable industrial systems, circular economy, resource use, resource efficiency, waste management, recycling, reuse and forms of material and energy recovery, treatment, environmental assessments and planning, policies and regulations, risk assessment analysis, risk management, green technologies, industrial ecosystems, industrial ecology and business model innovation, in the following areas:

  • Multi-criteria, analytic network process,
  • Fuzzy set, fuzzy inference, fuzzy multicriteria,
  • Interval valued fuzzy sets,
  • Interval valued intuitionistic fuzzy set,
  • Intuitionistic fuzzy sets,
  • Pythagorean fuzzy sets,
  • Interval-valued Pythagorean fuzzy sets,
  • Neutrosophic sets,
  • Interval valued q-rung orthopair fuzzy sets,
  • Hesitant fuzzy sets,
  • Interval type-2 fuzzy sets,
  • Spherical fuzzy sets,
  • Neuro-fuzzy,
  • Neural networks,
  • Neurocomputing,
  • Algorithm genetics,
  • Evolution algorithms,
  • Particle swarm optimization (PSO),
  • Ant colony,
  • Chaos theory,
  • Artificial Intelligence (AI),
  • Machine learning,
  • Dynamic Systems,
  • Approximate reasoning,
  • Expert systems,
  • Machine learning,
  • Pattern recognition.

Prof. Fausto Cavallaro
Dr. Dragan Pamučar
Dr. Abbas Mardani
Dr. Jingzheng Ren
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Soft computing
  • Fuzzy sets
  • Multicriteria
  • Decision analysis
  • Circular economy
  • Sustainability
  • Waste management
  • Air pollution management
  • Natural resources
  • Green technologies
  • Industrial ecology

Published Papers (5 papers)

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Research

22 pages, 3127 KiB  
Article
Urban Competitiveness: Identification and Analysis of Sustainable Key Drivers (A Case Study in Iran)
by Hossein Komasi, Sarfaraz Hashemkhani Zolfani, Olegas Prentkovskis and Paulius Skačkauskas
Sustainability 2022, 14(13), 7844; https://0-doi-org.brum.beds.ac.uk/10.3390/su14137844 - 27 Jun 2022
Cited by 8 | Viewed by 1926
Abstract
From the mid-1990s onwards, the concept of competitiveness was introduced to firms at the level of countries, regions, and cities. It was used as an index of the success and superiority of places. The present study used quantitative (survey) and qualitative methods in [...] Read more.
From the mid-1990s onwards, the concept of competitiveness was introduced to firms at the level of countries, regions, and cities. It was used as an index of the success and superiority of places. The present study used quantitative (survey) and qualitative methods in the framework of the exploratory paradigm to achieve key driving variables affecting the competitiveness of Kermanshah. The present study was applied in terms of its purpose and descriptive–analytical nature and research method. The study’s statistical population consisted of experts related to the Kermanshah competitiveness index, which studied 30 experts using the snowball method. MICMAC software was used to analyze the research data. Findings indicated that out of a total of 54 variables affecting the competitiveness of Kermanshah, 11 variables were in this group, which were the role of Kermanshah city in the power structure (MIN1); geographical and strategic location (MIN4); national, regional, and local plans (MIN5); management (MIN6); clean and healthy air (ENV1); potential sources of soil and water (ENV2); security of space (SEC2); the agricultural sector (ECO7); domestic tourism (ECO16); foreign tourism (ECO17); and sustainable sources of income (ECO19). The final model of Kermanshah’s future competitiveness will be that in the first stage, if the government (administration and government structure), in the form of national, regional, and local programs, pays attention to the competitive advantages of places. Especially, in large cities, and eliminating regional inequalities and in the next stage, local government (officials, managers, and all planners as the executive department) will need to act in order to operationalize the competitiveness of the city. With the correct use of opportunities and potentials (economic, socio-cultural, environmental, and security), in the 20-year horizon, Kermanshah will be a city with national and even transnational competitiveness. Otherwise, in addition to burning opportunities and destroying the capabilities of Kermanshah, other places adjacent to Kermanshah province will gradually be involved in challenges; tensions; and economic, cultural, social, environmental, security, and other crises. Full article
(This article belongs to the Special Issue Advanced Soft Computing for Smart Practices of Circular Economy in the Era of Covid-19)
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13 pages, 1404 KiB  
Article
The COVID-19 Pandemic and Nature-Based Tourism, Scenario Planning Approach (Case Study of Nature-Based Tourism in Iran)
by Hossein Komasi, Sarfaraz Hashemkhani Zolfani and Fausto Cavallaro
Sustainability 2022, 14(7), 3954; https://0-doi-org.brum.beds.ac.uk/10.3390/su14073954 - 27 Mar 2022
Cited by 13 | Viewed by 3309
Abstract
The development of nature-based tourism is one of the most critical sectors of tourism, which is influenced by various economic, socio-cultural, and environmental factors. The COVID-19 pandemic has influenced all sectors of tourism, including nature-based tourism. The purpose of this article is to [...] Read more.
The development of nature-based tourism is one of the most critical sectors of tourism, which is influenced by various economic, socio-cultural, and environmental factors. The COVID-19 pandemic has influenced all sectors of tourism, including nature-based tourism. The purpose of this article is to identify the key drivers affecting the development of nature-based tourism and analyze future scenarios of nature-based tourism in Iran based on the uncertainties caused by the COVID-19 pandemic. Micmac and ScenarioWizard software programs were used to analyze the research findings. Many factors affect the development of nature-based tourism in Iran, which fall into two human and natural factors groups. Five factors are the key drivers influencing the development of nature-based tourism in Iran: national, regional and globaly safety (F2); economic stability (F8); private sector participation (F9), human crises such as diseases, wars, etc. (F16); national and international advertising (national and international (F17); and travel costs (F19). According to the future of the COVID-19 pandemic, the research results show that a total of 10 scenarios for the future of nature-based tourism in Iran are conceivable, which are presented in three groups. Full article
(This article belongs to the Special Issue Advanced Soft Computing for Smart Practices of Circular Economy in the Era of Covid-19)
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18 pages, 7287 KiB  
Article
An Integrated Variance-COPRAS Approach with Nonlinear Fuzzy Data for Ranking Barriers Affecting Sustainable Operations
by K. N. S. Venkata Ramana, Raghunathan Krishankumar, Maja Sudjicki Trzin, P. P. Amritha and Dragan Pamucar
Sustainability 2022, 14(3), 1093; https://0-doi-org.brum.beds.ac.uk/10.3390/su14031093 - 18 Jan 2022
Cited by 6 | Viewed by 1413
Abstract
Sustainability is becoming the core theme of every organization to protect the planet from the drastic effects of climate change. Many organizations have drastically changed their practices to encourage green habits for sustainable operations. Practitioners have discussed the difficulties in the literature owing [...] Read more.
Sustainability is becoming the core theme of every organization to protect the planet from the drastic effects of climate change. Many organizations have drastically changed their practices to encourage green habits for sustainable operations. Practitioners have discussed the difficulties in the literature owing to the adoption of sustainable aspects of environmental, economic and social paradigms in the organization. One can identify diverse barriers, and ranking them would help policy-makers plan their actions. Motivated by this claim, a new integrated approach with nonlinear fuzzy data is put forward in this paper. The nonlinear mapping of fuzzy data provides a better representation of uncertainty, which inspired the authors to use nonlinear data. Further, the attitudinal variance method is proposed for a weight assessment of the criteria that can handle hesitation effectively and consider each agent’s reliability. The Boran principle in the nonlinear context is used to calculate the reliability values. Complex proportional assessment (COPRAS), a popular ranking algorithm, is extended to nonlinear data for rationally ranking barriers that affect sustainable operations. An illustrative example exemplifies the usability of the approach, and a comparison/sensitivity analysis reveals the pros and cons of the framework. Full article
(This article belongs to the Special Issue Advanced Soft Computing for Smart Practices of Circular Economy in the Era of Covid-19)
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15 pages, 459 KiB  
Article
An Integrated Fuzzy Goal Programming—Theory of Constraints Model for Production Planning and Optimization
by Habib Zare, Mahyar Kamali Saraji, Madjid Tavana, Dalia Streimikiene and Fausto Cavallaro
Sustainability 2021, 13(22), 12728; https://0-doi-org.brum.beds.ac.uk/10.3390/su132212728 - 17 Nov 2021
Cited by 1 | Viewed by 2058
Abstract
Manufacturing companies are under constant pressure to optimize the economic sustainability of their production systems. Production planning and optimization is a well-established strategy for considering resource constraints and improving economic productivity. This study proposes an integrated fuzzy goal planning and the theory of [...] Read more.
Manufacturing companies are under constant pressure to optimize the economic sustainability of their production systems. Production planning and optimization is a well-established strategy for considering resource constraints and improving economic productivity. This study proposes an integrated fuzzy goal planning and the theory of constraints for production planning and optimization. To this end, a hybrid Delphi–Buckley method was used to identify the relevant goals and a paired matrix questionnaire was used to determine the fuzzy weights of the goals. Furthermore, a fuzzy bottleneck detection algorithm was used to deal with the bottlenecks. A case study in the cable industry is presented to demonstrate the applicability and exhibit the efficiency of the proposed model. The results indicate that production planning in the cable industry could experience less deviation, almost 11% less, from the goals by applying the fuzzy goal programming under the theory of constraints, compared to the traditional method or crisp-goal programming. Full article
(This article belongs to the Special Issue Advanced Soft Computing for Smart Practices of Circular Economy in the Era of Covid-19)
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24 pages, 1033 KiB  
Article
TOPSIS Method Based on Correlation Coefficient under Pythagorean Fuzzy Soft Environment and Its Application towards Green Supply Chain Management
by Rana Muhammad Zulqarnain, Xiao Long Xin, Imran Siddique, Waseem Asghar Khan and Mogtaba Ahmed Yousif
Sustainability 2021, 13(4), 1642; https://0-doi-org.brum.beds.ac.uk/10.3390/su13041642 - 03 Feb 2021
Cited by 72 | Viewed by 3096
Abstract
The correlation coefficient between two variables is an important aspect of statistics. The accuracy of assessments of correlation relies on information from a set of discourses. Data collected in statistical studies are often full of exceptions. Pythagorean fuzzy soft sets (PFSS) are a [...] Read more.
The correlation coefficient between two variables is an important aspect of statistics. The accuracy of assessments of correlation relies on information from a set of discourses. Data collected in statistical studies are often full of exceptions. Pythagorean fuzzy soft sets (PFSS) are a parametrized family of extended Pythagorean fuzzy sets (PFS). They comprise a generalization of intuitionistic fuzzy soft sets which may be used to accurately assess deficiencies and uncertainties in evaluations. PFSS can accommodate uncertainty more competently than intuitionistic fuzzy soft sets and are the most important strategy when dealing with fuzzy information in decision-making processes. Herein, the concept and characteristics of correlation coefficients and the weighted correlation coefficients in PFSS are discussed. We also introduce the Pythagorean fuzzy soft weighted average (PFSWA) and Pythagorean fuzzy soft weighted geometric (PFSWG) operators and discuss their desirable characteristics. A prioritization technique for order preference by similarity to the ideal solution (TOPSIS) under the PFSS environment based on correlation coefficients and weighted correlation coefficients will be introduced. Through the proposed methodology, a technique for decision-making is developed. Additionally, an application of the proposed TOPSIS technique is presented for green supplier selection in green supply chain management (GSCM). The practicality, efficacy, and flexibility of the proposed approach is proved through comparative analyses, drawing upon existing studies. Full article
(This article belongs to the Special Issue Advanced Soft Computing for Smart Practices of Circular Economy in the Era of Covid-19)
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