Fuzzy Constrained Shortest Path Problem for Location-Based Online Services

Sori, Ali Abbaszadeh; Ebrahimnejad, Ali; Motameni, Homayun; Verdegay, J. L.

doi:10.1142/s0218488521500116

Cited by 11 publications

(6 citation statements)

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“…ey considered mixed interval fuzzy numbers for the arc weights. Sori et al [29] studied the constrained shortest path problem in locationbased online services to find a path with the lowest cost with fuzzy time and cost. e summary of the last works is presented in Table 1.…”

Section: Literature Reviewmentioning

confidence: 99%

EFP‐GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty

2022

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The aviation industry is one of the most widely used applications in transportation. Due to the limited capacity of aircraft, revenue management in this industry is of high significance. On the other hand, the hub location problem has been considered to facilitate the demands assignment to hubs. This paper presents an integrated p-hub location and revenue management problem under uncertain demand to maximize net revenue and minimize total cost, including hub establishment and transportation costs. A fuzzy programming model and a genetic algorithm are developed to solve the proposed model with different sizes. The mining and petroleum industry is used for case studies. Results show that the proposed algorithm can obtain a suitable solution in a reasonable amount of time.

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Section: Literature Reviewmentioning

confidence: 99%

EFP‐GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty

2022

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“…Another advantage of FLS is that expert knowledge and engineer experience is important references for fuzzy logic control [45]- [47]. Meanwhile, relevant recent researches shows that the fuzzy set theory has wide applications in the field of multi-criteria decision making (MCDM), linear programming (LP), control of robot, Shortest Path planning and dealing with uncertainty [51]- [53]. Furthermore, FLS may exports continuous control signal based on the discrete membership functions and fuzzy rules.…”

Section: Adaptive Design Of Experimentsmentioning

confidence: 99%

Hierarchical Multi-Objective Optimization of Automobile Seat Frame Based on Grey Fuzzy Logic System

Wang

Lan²,

Long

2022

IEEE Access

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In development of the automobile industry, lightweight and safety performance are contradictory, yet they are of great significance.The optimization process of auto parts is a high-dimensional optimization problem which has a variety of regulations limits and safety tests at the same time. In order to address this issue, hierarchical multi-objective optimization of a passenger car seat frame is carried out in this research. Different from previous researches, in this paper, all car seat frame parts are listed as the optimization objects and are given different optimized attributes. Meanwhile, in order to achieve the goal of effectively reducing the sample sizes of the design of experiments, hierarchical optimization is proposed, and the optimization process is divided into three stages. In each stage, components with different optimized attributes are introduced into various safety tests and then conducting design of experiments. On the other hand, through adopting the grey fuzzy logic system to assign the appropriate optimized grade, the optimization process is simplified and the errors caused by the manual selection or unified optimization levels are avoided. The proposed method is considered to be an universal approach to solve the lightweight optimization of the auto parts. Design parameters of the car seat frame before and after the hierarchical multi-objective optimization are compared, it illustrated that total mass and material cost of the seat frame are reduced by 2.3kg (28.5%) and 13.8 (32.4%) respectively. Moreover, various comparisons are carried out to verify the validity of the optimization method proposed in this paper. In conclusion, the proposed method is quite promising yet with less sample points associated, is an effective mean to solve the multi-objective optimization problems of automobile component. INDEX TERMSAutomobile seat frame lightweight, hierarchical multi-objective optimization, adaptive design of experiments, grey fuzzy logic system.

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“…Therefore, relief services face problems such as rapid changes in information, high-urgency requests and low quality in former information. VRP in the context of uncertainty is a practical decision, which is applied in many other real-world situations such as location-based online services or route planning of robots (Sori et al, 2019(Sori et al, , 2021, which can be applied in disasterbased routing services.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

“…VRP in the context of uncertainty is a practical decision, which is applied in many other real-world situations such as location-based online services or route planning of robots (Sori et al. , 2019, 2021), which can be applied in disaster-based routing services.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Vehicle routing problem for humanitarian relief distribution under hybrid uncertainty

Nodoust

Pishvaee

Seyedhosseini

2021

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PurposeGiven the importance of estimating the demand for relief items in earthquake disaster, this research studies the complex nature of demand uncertainty in a vehicle routing problem in order to distribute first aid relief items in the post disaster phase, where routes are subject to disruption.Design/methodology/approachTo cope with such kind of uncertainty, the demand rate of relief items is considered as a random fuzzy variable and a robust scenario-based possibilistic-stochastic programming model is elaborated. The results are presented and reported on a real case study of earthquake, along with sensitivity analysis through some important parameters.FindingsThe results show that the demand satisfaction level in the proposed model is significantly higher than the traditional scenario-based stochastic programming model.Originality/valueIn reality, in the occurrence of a disaster, demand rate has a mixture nature of objective and subjective and should be represented through possibility and probability theories simultaneously. But so far, in studies related to this domain, demand parameter is not considered in hybrid uncertainty. The worth of considering hybrid uncertainty in this study is clarified by supplementing the contribution with presenting a robust possibilistic programming approach and disruption assumption on roads.

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Fuzzy Constrained Shortest Path Problem for Location-Based Online Services

Cited by 11 publications

References 0 publications

EFP‐GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty

EFP‐GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty

Hierarchical Multi-Objective Optimization of Automobile Seat Frame Based on Grey Fuzzy Logic System

Vehicle routing problem for humanitarian relief distribution under hybrid uncertainty

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