Handling uncertainty in route choice models: From probabilistic to possibilistic approaches

Henn, Vincent; Ottomanelli, Michele

doi:10.1016/j.ejor.2005.02.026

Cited by 52 publications

(15 citation statements)

References 26 publications

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“…The fuzzy sets can be helpful for these kinds of situations [12][13][14]. The initial concept about fuzzy sets is suggested in [15] to the literature and use of fuzzy sets has rapidly spread out many research and application area in spite of the negative reactions at the beginning.…”

Section: Simulation and Fuzzy Sets For Determination Of The Project Rmentioning

confidence: 99%

An integrated decision support approach for project investors in risky and uncertain environments

Armaneri

Özdağoğlu

Yalçınkaya

2010

Journal of Computational and Applied Mathematics

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a b s t r a c tIn project investment decisions, it is often assumed that estimated values of project parameters are certain and they would not deviate by the time. However, project parameters normally change during a life cycle of the project. Therefore, an existence of a deviation or gap between forecasted values and actual values is inevitable. Because of the uncertainty of the future, forecasting the true and exact values of project parameters is almost impossible. In this study, an integrated decision support approach based on simulation and fuzzy set theory is proposed for project investors in risky and uncertain environments. This approach determines the risk levels of the projects and helps investors to make investment decisions. In the scope of the study, a flowchart is presented to guide to decision maker in different situations of information uncertainty that belongs to project parameter values. Via this flowchart, the values of project parameters can be chosen depending on how they are determined (deterministic, stochastic or fuzzy) by project analyst. Besides, calculating and analyzing the project risk in all possible situations would be easier. Illustrative examples are given to demonstrate the application of this approach.

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Section: Simulation and Fuzzy Sets For Determination Of The Project Rmentioning

confidence: 99%

An integrated decision support approach for project investors in risky and uncertain environments

Armaneri

Özdağoğlu

Yalçınkaya

2010

Journal of Computational and Applied Mathematics

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“…Zimmermann (2000) suggests an approach to determine, in a context dependent manner, a suitable method to model uncertainty in applications, such as inventory planning. Henn and Ottomanelli (2006) analyze how uncertainty affects the drivers' route choice process in traffic assignment models and discuss the adequacy of deterministic and stochastic models in supporting traffic assignment calculations. Shutz et al (2009) examine how the use of stochastic models of demand influences strategic capacity and location decisions in a meat processing supply chain as compared to using a deterministic model.…”

Section: Related Literaturementioning

confidence: 99%

Strategic analysis of technology and capacity investments in the liquefied natural gas industry

Sönmez

Kekre

Scheller‐Wolf

et al. 2013

European Journal of Operational Research

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“…They were mainly related to fuzzy mathematical programming (Mohamed and Cote 1999;Chanas and Zielinski 2000), stochastic programming (Bennett, James, McKone and Oldenburg 1998;Henn and Ottomanelli 2006), chance-constrained programming (Birge and Louveaux 1997) and interval programming (Sae-Lim 1999). In the probabilistic (stochastic) approach, probability distributions are used to describe random variability in modeling parameters.…”

mentioning

confidence: 99%

An interval-parameter mixed integer multi-objective programming for environment-oriented evacuation management

Huang

Yan

et al. 2010

International Journal of Systems Science

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Large crowds are increasingly common at political, social, economic, cultural and sports events in urban areas. This has led to attention on the management of evacuations under such situations. In this study, we optimise an approximation method for vehicle allocation and route planning in case of an evacuation. This method, based on an interval-parameter multi-objective optimisation model, has potential for use in a flexible decision support system for evacuation management. The modeling solutions are obtained by sequentially solving two sub-models corresponding to lower-and upper-bounds for the desired objective function value. The interval solutions are feasible and stable in the given decision space, and this may reduce the negative effects of uncertainty, thereby improving decision makers' estimates under different conditions. The resulting model can be used for a systematic analysis of the complex relationships among evacuation time, cost and environmental considerations. The results of a case study used to validate the proposed model show that the model does generate useful solutions for planning evacuation management and practices. Furthermore, these results are useful for evacuation planners, not only in making vehicle allocation decisions but also for providing insight into the tradeoffs among evacuation time, environmental considerations and economic objectives.

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Handling uncertainty in route choice models: From probabilistic to possibilistic approaches

Cited by 52 publications

References 26 publications

An integrated decision support approach for project investors in risky and uncertain environments

An integrated decision support approach for project investors in risky and uncertain environments

Strategic analysis of technology and capacity investments in the liquefied natural gas industry

An interval-parameter mixed integer multi-objective programming for environment-oriented evacuation management

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