Effect of variable carbon emission in a multi-objective transportation-p-facility location problem under neutrosophic environment

Das, Soumen Kumar; Roy, Sankar Kumar

doi:10.1016/j.cie.2019.04.037

Cited by 84 publications

(35 citation statements)

References 31 publications

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“…In the figure, if one bar can be seen from the top of another bar, then these two bars are linked, and the corresponding vertices in the associated visibility graph are also directly linked. For example, there is a visibility relationship between the two time series data (1,60) and (3,40) because there is a single time series data point (2,30) between them and 30 < (40…”

Section: Preliminariesmentioning

confidence: 99%

“…Therefore, there is a direct link between time nodes t 1 and t 3 in the visibility graph. By contrast, because there is a time series data point (4,60) between (3,40) and (5,30) and 60 > (30 + (40 − 30) × (5 − 4)/(5 − 3)), the visibility criterion is not fulfilled for these points, meaning that there is no direct link between t 3 and t 5 in the visibility graph.…”

Section: Preliminariesmentioning

confidence: 99%

“…Considering the current limitations imposed by the mercurial trends observed in time series from real-world applications and inspired by methods of fuzzy and interval time series analysis [37]- [39], we have explored the concept of information uncertainty and noted that a direct prediction approach may not be the best choice [40], [41]. Recent studies have presented various approaches for addressing different types of uncertainty [42]- [45].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation

Liu

Xiao

Lin

et al. 2020

IEEE Trans. Fuzzy Syst.

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Forecasting time series is an emerging topic in operational research. Existing time series models have limited prediction accuracy when faced with the characteristics of nonlinearity and nonstationarity in complex situations related to energy and finance. To enhance overall prediction capabilities and improve forecasting accuracy, we propose a fuzzy interval time series forecasting model on the basis of network-based multiple time-frequency spaces and the induced ordered weighted averaging aggregation (IOWA) operation. Specifically, a time series signal is decomposed into ensemble empirical modes and then reconstructed as various time-frequency spaces, which are transformed into visibility graphs. Then, forecasting intervals in different spaces can be collected after the local random walker link prediction model is adopted. Furthermore, a rule-based representation value function inspired by Yager's golden rule approach is defined, and an appropriate representation value is calculated. Finally, after IOWA is used to aggregate the forecasting outcomes in different time-frequency spaces, the final forecast value can be obtained from the fuzzy forecasting interval. Considering that energy issues are of widespread interest in nature and the social economy, two cases, based on a hydrological time series from the Biliuhe River in China and two wellknown sets of financial time series data, TAIEX and HSI, are studied to test the performance of the proposed approach in comparison with existing models. Our results show that the proposed approach can achieve better performance than well-developed models.

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Section: Preliminariesmentioning

confidence: 99%

Section: Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation

Liu

Xiao

Lin

et al. 2020

IEEE Trans. Fuzzy Syst.

View full text Add to dashboard Cite

show abstract

“…They considered the transportation and installation costs as the economic objective, the emissions from transportation and operations as the environmental objective, and the efficiency of processing plants as the technological objective. In addition, Das and Roy [22] presented a multi-objective transportation-p-facility location problem that integrates the FLP and the transportation problem. In this study, three objectives, including the total transportation costs, transportation time, and carbon emission costs, were considered.…”

Section: The Multi-objective Flpmentioning

confidence: 99%

Efficient Allocation of Customers to Facilities in the Multi-Objective Sustainable Location Problem

Xi-feng

2020

Sustainability

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This paper aims to evaluate the impact of customer allocation on the facility location in the multi-objective location problem for sustainable logistics. After a new practical multi-objective location model considering vehicle carbon emissions is introduced, the NSGA-II and SEAMO2 algorithms are employed to solve the model. Within the framework of each algorithm, three different allocation rules derived from the optimization of customer allocation based on distance, cost, and emissions are separately applied to perform the customer-to-facility assignment so as to evaluate their impacts. The results of extensive computational experiments show that the allocation rules have nearly no influence on the solution quality, and the allocation rule based on the distance has an absolute advantage of computation time. These findings will greatly help to simplify the location-allocation analysis in the multi-objective location problems.

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“…A study on time-dependent fuzzy random location-scheduling transportation programming for hazardous materials has been done by Meiyi et al [18]. In connection with minimizing pollution, a number of studies has been entitled by researchers such as Dulebenets [19], Das and Roy [20], Jalalian et al [21], Dulebenets [22], and many others. Ebrahimnejad [23] proposed an improved approach for solving fuzzy TP with triangular fuzzy numbers.…”

Section: Review Of Related Workmentioning

confidence: 99%

Time Variant Multi-Objective Interval-Valued Transportation Problem in Sustainable Development

2019

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Sustainable development is treated as the achievement of continued economic development without detriment to environmental and natural resources. Now-a-days, in a competitive market scenario, most of us are willing to pay less and to gain more in quickly without considering negative externalities for the environment and quality of life for future generations. Recalling this fact, this paper explores the study of time variant multi-objective transportation problem (MOTP) with consideration of minimizing pollution. Time of transportation is of utmost importance in reality; based on this consideration, we formulate a MOTP, where we optimize transportation time as well as the cost function. The parameters of MOTP are interval-valued, so this form of MOTP is termed as a multi-objective interval transportation problem (MOITP). A procedure is taken into consideration for converting MOITP into deterministic form and then for solving it. Goal programming is applied to solve the converted transportation problem. A case study is conducted to justify the methodology by utilizing the environmental impact. At last, conclusions and future research directions are included regarding our study.

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Effect of variable carbon emission in a multi-objective transportation-p-facility location problem under neutrosophic environment

Cited by 84 publications

References 31 publications

A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation

A Fuzzy Interval Time-Series Energy and Financial Forecasting Model Using Network-Based Multiple Time-Frequency Spaces and the Induced-Ordered Weighted Averaging Aggregation Operation

Efficient Allocation of Customers to Facilities in the Multi-Objective Sustainable Location Problem

Time Variant Multi-Objective Interval-Valued Transportation Problem in Sustainable Development

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