Foundations of semialgebraic gene-environment networks

Kropat, Erik; Weber, Gerhard; Tirkolaee, Erfan Babaee

doi:10.3934/jdg.2020018

Cited by 20 publications

(5 citation statements)

References 48 publications

(56 reference statements)

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“…Application of uncertainty and forecasting techniques such as robust optimization (Golpîra and Tirkolaee, 2019; Kara et al, 2019; Khalilpourazari et al, 2020a; Lotfi et al, 2020; Özmen et al, 2017), fuzzy programming (Goli et al, 2021; Maity et al, 2019; Roy et al, 2019; Tirkolaee et al, 2021), stochastic optimal control (Kalaycı et al, 2020; Kropat et al, 2020; Savku and Weber, 2018), time series (Weber et al, 2011), regression models (Kuter et al, 2018), and grey systems (Ergün et al, 2020) to address the uncertain nature of the problem.…”

Section: Discussionmentioning

confidence: 99%

A sustainable medical waste collection and transportation model for pandemics

Tirkolaee

Aydın

2021

Waste Manag Res

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We are currently experiencing a critical period for the prevention and control of the COVID-19 pandemic. COVID-19 related waste is a threat to global public environmental health. Medical waste management during this pandemic is one of the major issues facing public service organizations such as municipalities, which is of great importance in terms of logistics, environment and social aspects. The discussion of logistics operations is related to the collection, transportation and disposal of waste, which imposes high expenses. Many methods have been applied to develop and improve waste management policies in the literature. Apart from these studies, very few researchers have improved vehicle operations in waste management considering environmental aspects and the possibility of outsourcing. In this paper, by examining the gaps in the field, we try to explain and formulate the sustainable medical waste management problem for pandemics. Finally, by designing several practical examples with different scales, we solve the problem using CPLEX solver, compare different conditions and discuss the practical implications using the sensitivity analysis of demand parameter.

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Section: Discussionmentioning

confidence: 99%

A sustainable medical waste collection and transportation model for pandemics

Tirkolaee

Aydın

2021

Waste Manag Res

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“…Besides the application of the hostility measure in those fields, it could also perform in different domains like, for example, Big Data, to check if the condensation of data is rich enough to substitute the original data [12]. Also, an adapted version of the hostility could be applied to obtain useful information to enrich the modeling phase in targetenvironment networks that arises in fields like genetics and economics [19].…”

Section: Lessons Learnedmentioning

confidence: 99%

Hostility measure for multi-level study of data complexity

et al. 2022

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Complexity measures aim to characterize the underlying complexity of supervised data. These measures tackle factors hindering the performance of Machine Learning (ML) classifiers like overlap, density, linearity, etc. The state-of-the-art has mainly focused on the dataset perspective of complexity, i.e., offering an estimation of the complexity of the whole dataset. Recently, the instance perspective has also been addressed. In this paper, the hostility measure, a complexity measure offering a multi-level (instance, class, and dataset) perspective of data complexity is proposed. The proposal is built by estimating the novel notion of hostility: the difficulty of correctly classifying a point, a class, or a whole dataset given their corresponding neighborhoods. The proposed measure is estimated at the instance level by applying the k-means algorithm in a recursive and hierarchical way, which allows to analyze how points from different classes are naturally grouped together across partitions. The instance information is aggregated to provide complexity knowledge at the class and the dataset levels. The validity of the proposal is evaluated through a variety of experiments dealing with the three perspectives and the corresponding comparative with the state-of-the-art measures. Throughout the experiments, the hostility measure has shown promising results and to be competitive, stable, and robust.

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“…Tirkolaee et al [53] identified the contributions of ML techniques in selecting and segmenting suppliers, predicting supply chain risks, and estimating demand and sales, production, inventory management, transportation and distribution, sustainable development (SD), and circular economy (CE). Kropat et al [54] proposed a novel framework of semialgebraic gene-environment networks. Khalilpourazari and Doulabi [55] showed that the offered robust model handles uncertainties more efficiently and finds solutions that have significantly lower costs and delivery time.…”

Section: Supply Chainmentioning

confidence: 99%

Optimal Decision and Coordination of Organic Food Supply Chain from the Perspective of Blockchain

Ding

Bai

2022

Discrete Dynamics in Nature and Society

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Driven by the pain points of the organic food supply chain, which has been plagued by counterfeiting and difficulties in pursuing accountability, this paper investigates a secondary organic food supply chain consisting of suppliers and retailers and establishes two supply chain models under the traditional model and in the blockchain traceability context. In order to effectively solve the problem of unrealized Pareto improvement in organic food supply chain after applying blockchain, a new hybrid contract based on benefit-sharing and cost-sharing is designed to coordinate the supply chain and realize Pareto improvement, and this solution is gradually applied to organic food enterprises. Based on the fact that blockchain can improve trust in the supply chain and eliminate counterfeiting of organic food, the relationship between the rate of genuine products and market demand and the cost of blockchain is established, and then the analysis is developed using the Stackelberg game. We compare the traditional model with the model in the blockchain context and analyze the optimal profit of each supply chain entity, comparing the change in optimal profit before and after the blockchain implementation, and clarifying the cost threshold of the blockchain technology input application. We find that: (i) The adoption of blockchain can not only improve the authenticity of products and combat counterfeit and shoddy organic food, but at the same time, the improvement of organic level in the context of blockchain will also attract some consumers to buy organic food, which will increase the main body of the supply chain and the overall profit. (ii) Blockchain-adopted supply chains are consistently more profitable for all parties and overall than traditional supply chains. The main contribution of this study is that in the organic food supply chain under the application of blockchain technology model, by introducing revenue-sharing and cost-sharing contracts, the profit between each member of the organic food supply chain is further improved than the traditional model, and also, all of them are optimized, which further improves the stability of the supply chain and brings the supply chain to a coordinated state. Finally, in this context, the obtained results show the effectiveness and realistic operational efficiency of the proposed approach for companies compared to traditional single revenue-sharing covenants. A combination of revenue-sharing and cost-sharing covenants is the best approach to solve such problems. In conclusion, it should be noted that the analysis presented in this study will help decision makers choose the most appropriate option among the possible solutions according to their criteria. This proposed framework can also be extended in various cases where profits are out of balance in the organic food supply chain, such as safety and value gain.

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Foundations of semialgebraic gene-environment networks

Cited by 20 publications

References 48 publications

A sustainable medical waste collection and transportation model for pandemics

A sustainable medical waste collection and transportation model for pandemics

Hostility measure for multi-level study of data complexity

Optimal Decision and Coordination of Organic Food Supply Chain from the Perspective of Blockchain

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