Related references
Note: Only part of the references are listed.
Article
Operations Research & Management Science
Shyamali Ghosh et al.
Summary: An integrated multi-objective environment is investigated in this paper to evaluate a waste management problem in order to develop sustainability. Three objective functions are optimized, including cost, time, and carbon emission. Cap and trade policy is used to reduce carbon emission and provide economic opportunities. A strategy is proposed to optimize sustainability factors in solid waste management. Numerical problems are evaluated using advanced methods and Pareto-optimal solutions are obtained, suggesting the complexity of applying cap and trade policy or waste management in real-world situations. The overall conclusion recommends utilizing carbon policies to minimize carbon emissions and establish waste management projects based on sustainability.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Xiao-Hong Pan et al.
Summary: Serving as a promising solution to manage municipal solid waste (MSW), the waste-to-energy (WTE) system has recently received increasing attention. This paper proposes a novel interval type-2 fuzzy decision-making framework to support the site selection of the WTE system. The framework includes establishing a sustainable evaluation index system, developing information transformation mechanisms, and using an interval type-2 fuzzy ORESTE method to analyze conflicts and select the most desirable site.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Gholamreza Haseli et al.
Summary: In sustainable waste supply chains, selecting recycling partners is crucial. A framework that considers both sustainability and resilience factors is developed to improve the decision-making process. Multi-criteria decision-making methods are useful tools, but the capability to support efficient group decision-making has been a disadvantage. Therefore, a novel approach using ZE-numbers and a combined compromise solution is proposed.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Hongguang Wu et al.
Summary: This paper proposes a new optimization algorithm called ACO-DR based on the ant colony optimization (ACO) to solve the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Window (VRPSPDTW). ACO-DR improves the search probability and global search ability by designing a random transition rule and introducing destroy and repair strategies to avoid falling into local optima. Experimental results show that ACO-DR outperforms state-of-the-art algorithms on Solomon benchmark and Gehring-Homberge benchmark, providing an effective solution for VRPSPDTW problem.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Kazi Wahadul Hasan et al.
Summary: The benefits of the circular economy are driving industries to form closed-loop supply chains (CLSCs) that minimize cost and environmental impact. However, disruptions in the production process hinder the attainment of these objectives. This study develops a complex mathematical model to minimize total cost, energy consumption, CO2 emissions, and waste generation by considering disruption risks. Three existing heuristics and an updated hyper-heuristic algorithm are employed to compare their efficiency and effectiveness. The results show that CLSCs can mitigate production shortages and reduce costs, energy consumption, CO2 emissions, and waste generation.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Gaurav Srivastava et al.
Summary: This paper addresses a variant of the vehicle routing problem with time windows and proposes two evolutionary approaches to maximize the quality of service delivered to the customer. The proposed approaches incorporate various heuristics and provide better initial solutions compared to random solutions. Experimental results show that the proposed approaches outperform the state-of-the-art approach in terms of solution quality and execution time. (c) 2022 Elsevier B.V. All rights reserved.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Zhenyu Zhang et al.
Summary: Freight transport is identified as the main contributor to carbon emissions. Implementing zero-carbon measures in freight transport is crucial for sustainable development. The study proposes an interval 2-tuple linguistic multi-attribute decision-making approach to prioritize zero-carbon measures. The developed decision model considers the uncertainty evaluation information and effectively ranks the measures.
APPLIED SOFT COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Muhammed Bilal Horasan et al.
Summary: The rapid increase in world population and global economic growth have led to serious issues related to energy consumption. Therefore, it is important to conduct a comprehensive analysis of the current and potential energy situation in order to develop effective global and regional energy strategies. This study presents a multi-objective decision-making model for renewable energy planning, focusing on five renewable energy sources, and determines the most appropriate resource diversity for Turkey. The results indicate that solar and hydroelectric energies should be the main sources to meet the energy demand.
Article
Computer Science, Artificial Intelligence
Shyamali Ghosh et al.
Summary: Waste management plays an important role in various fields of the global ecosystem, contributing to a greener environment and sustainable development. In this study, a multi-objective solid transportation model is proposed for waste management in the agriculture and forest departments, targeting urban and rural development. The objective functions considered in this model are transportation cost, job opportunities, and carbon emissions. Carbon emissions are constrained by a combination of carbon mechanisms including carbon tax, cap-and-trade, and offset policies. Realistic processes often involve various critical situations and uncertainty in related data, for which a Pythagorean hesitant fuzzy environment is preferred over single uncertainty. A ranking approach is then used to convert uncertain data into crisp data. Two industrial applications are studied to validate the model and select the best carbon mechanism policy, utilizing fuzzy programming and Pythagorean hesitant fuzzy programming to derive the Pareto-optimal solutions. The study includes comparative analysis, model validation, sensitivity analysis, managerial insights, and conclusions, along with future research directions.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Automation & Control Systems
Shyamali Ghosh et al.
Summary: The motive of this study is to validate the effectiveness of preserving perishable items in a transportation system. We introduce a preservation technology (PT) with cost to decrease the deterioration rate and extend the lifetime of the items. By initiating a multi-objective transportation problem connected with PT, we consider various criteria such as transportation cost, preservation cost, time, and deterioration under a Pythagorean fuzzy environment. Two numerical examples are presented to demonstrate the applicability of our approach, which is solved using the epsilon-constraint method, neutrosophic linear programming, and fuzzy TOPSIS approach.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Binoy Krishna Giri et al.
Summary: This paper introduces two methods for solving a multi-objective green 4-dimensional fixed-charge transportation problem under neutrosophic environment, focusing on minimizing transportation cost, carbon emission, and transportation time. The methods involve using single valued trapezoidal neutrosophic number for modeling and applying neutrosophic programming and Pythagorean hesitant fuzzy programming to extract a better compromise solution. The applicability and validity of the proposed problem are demonstrated through comparisons of compromise solutions derived from the programming methods.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Amiya Biswas et al.
Summary: The COVID-19 pandemic has presented challenges for transportation companies due to travel restrictions. This study aims to solve a fixed-charge transportation problem during the pandemic and minimize transportation costs between regions with high restrictions. The Genetic Algorithm is used with new operators to handle multiple trips and capacity constraints.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Kangyin Dong et al.
Summary: This paper examines the changes and driving factors of global ICT-embodied CO2 emissions using the multi-regional input-output (MRIO) method and structural decomposition analysis (SDA) method. The results indicate that CO2 emissions intensity and final demand composition are the main factors influencing ICT-embodied CO2 emissions. Furthermore, heterogeneity in countries and sectors has an impact on ICT-embodied CO2 emissions. However, it is challenging for most countries to reach the peak of ICT-embodied CO2 emissions before 2050 under the current development pattern.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Shyamali Ghosh et al.
Summary: This paper aims to integrate solid transportation problem, budget constraints, and carbon emission with maximum profit by using multi-objective decision making. The study utilizes neutrosophic environment and methods such as neutrosophic linear programming, fuzzy programming, and global criterion to find the compromise solution for the transportation problem. The performance of the model is evaluated through a numerical example and the results are compared.
Article
Computer Science, Artificial Intelligence
Sudipta Midya et al.
Summary: This research focuses on addressing the multi-stage multi-objective fixed-charge solid transportation problem with a green supply chain network system in an intuitionistic fuzzy environment. The study utilizes trapezoidal intuitionistic fuzzy numbers and the expected value operator to convert the problem into a deterministic one, and then solves it using weighted Tchebycheff metrics programming and min-max goal programming to provide Pareto-optimal solutions.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Operations Research & Management Science
Shyamali Ghosh et al.
Summary: In this paper, an efficient model of multi-objective product blending fixed-charge transportation problem with truck load constraints through transfer station is proposed. The model considers extra costs, transportation costs, and incorporates a fuzzy-rough environment to handle uncertainties in the parameters. The model is tested using fuzzy programming, neutrosophic linear programming, and global criteria method, with numerical examples illustrating its applicability.
RAIRO-OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Arijit Mondal et al.
Summary: Logistics problems are crucial during emergencies, especially during a critical situation like the COVID-19 pandemic. This paper proposes a multi-objective multi-product multi-period two-stage sustainable supply chain planning to maintain supply during the pandemic. By considering uncertain-random parameters, a robust optimization approach is utilized to deal with different scenarios, with a multi-attribute decision making approach determining priority areas based on urgency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Environmental
Erfan Babaee Tirkolaee et al.
WASTE MANAGEMENT & RESEARCH
(2020)
Article
Engineering, Environmental
Erfan Babaee Tirkolaee et al.
Article
Green & Sustainable Science & Technology
Zhanna Mingaleva et al.
Article
Computer Science, Artificial Intelligence
Faruk Karaaslan et al.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2020)
Article
Computer Science, Artificial Intelligence
Seyed Farid Ghannadpour et al.
APPLIED SOFT COMPUTING
(2020)
Article
Computer Science, Artificial Intelligence
Bahram Farhadinia et al.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2020)
Article
Green & Sustainable Science & Technology
Pradeep Rathore et al.
JOURNAL OF CLEANER PRODUCTION
(2019)
Article
Engineering, Environmental
Erfan Babaee Tirkolaee et al.
WASTE MANAGEMENT & RESEARCH
(2019)
Article
Green & Sustainable Science & Technology
Farzad Mahmoudsoltani et al.
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Green & Sustainable Science & Technology
Masoud Rabbani et al.
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Green & Sustainable Science & Technology
Syed Mohd Muneeb et al.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2018)
Article
Computer Science, Artificial Intelligence
Peide Liu et al.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2017)
Article
Engineering, Environmental
Zhitao Xu et al.
