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Elevator planning with stochastic multicriteria acceptability analysis

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  • Tervonen, Tommi
  • Hakonen, Henri
  • Lahdelma, Risto

Abstract

Modern elevator systems in high-rise buildings consist of groups of elevators with centralized control. The goal in elevator planning is to configure a suitable elevator group to be built. The elevator group must satisfy specific minimum requirements for a number of standard performance criteria. In addition, it is desirable to optimize the configuration in terms of other criteria related to the performance, economy and service level of the elevator group. Different stakeholders involved in the planning phase emphasize different criteria. Most of the criteria measurements are by nature uncertain. Some criteria can be estimated by using analytical models, while others, especially those related to the service level in different traffic patterns, require simulations. In this paper we formulate the elevator planning problem as a stochastic discrete multicriteria decision-making problem. We compare 10 feasible elevator group configurations for a 20-floor building. We evaluate the criteria related to the service level in different traffic situations using the KONE Building Traffic Simulator, and use analytical models and expert judgments for other criteria. The resulting decision problem contains mixed type criteria. Some criteria are represented by the multivariate Gaussian distribution, others by deterministic values and ordinal (ranking) information. To identify configurations that can best satisfy the goals of the stakeholders, we analyze the problem using the stochastic multicriteria acceptability analysis (SMAA) method.

Suggested Citation

  • Tervonen, Tommi & Hakonen, Henri & Lahdelma, Risto, 2008. "Elevator planning with stochastic multicriteria acceptability analysis," Omega, Elsevier, vol. 36(3), pages 352-362, June.
    • Handle: RePEc:eee:jomega:v:36:y:2008:i:3:p:352-362
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    References listed on IDEAS

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    1. Lahdelma, Risto & Hokkanen, Joonas & Salminen, Pekka, 1998. "SMAA - Stochastic multiobjective acceptability analysis," European Journal of Operational Research, Elsevier, vol. 106(1), pages 137-143, April.
    2. Lahdelma, Risto & Miettinen, Kaisa & Salminen, Pekka, 2003. "Ordinal criteria in stochastic multicriteria acceptability analysis (SMAA)," European Journal of Operational Research, Elsevier, vol. 147(1), pages 117-127, May.
    3. Risto Lahdelma & Pekka Salminen, 2001. "SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making," Operations Research, INFORMS, vol. 49(3), pages 444-454, June.
    4. Lahdelma, Risto & Makkonen, Simo & Salminen, Pekka, 2006. "Multivariate Gaussian criteria in SMAA," European Journal of Operational Research, Elsevier, vol. 170(3), pages 957-970, May.
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    Cited by:

    1. R. Pelissari & M. C. Oliveira & S. Ben Amor & A. Kandakoglu & A. L. Helleno, 2020. "SMAA methods and their applications: a literature review and future research directions," Annals of Operations Research, Springer, vol. 293(2), pages 433-493, October.
    2. Fan, Zhi-Ping & Liu, Yang & Feng, Bo, 2010. "A method for stochastic multiple criteria decision making based on pairwise comparisons of alternatives with random evaluations," European Journal of Operational Research, Elsevier, vol. 207(2), pages 906-915, December.
    3. Lahdelma, Risto & Salminen, Pekka, 2009. "Prospect theory and stochastic multicriteria acceptability analysis (SMAA)," Omega, Elsevier, vol. 37(5), pages 961-971, October.
    4. Kadziński, Miłosz & Tervonen, Tommi, 2013. "Robust multi-criteria ranking with additive value models and holistic pair-wise preference statements," European Journal of Operational Research, Elsevier, vol. 228(1), pages 169-180.
    5. Corrente, Salvatore & Figueira, José Rui & Greco, Salvatore & Słowiński, Roman, 2017. "A robust ranking method extending ELECTRE III to hierarchy of interacting criteria, imprecise weights and stochastic analysis," Omega, Elsevier, vol. 73(C), pages 1-17.
    6. Durbach, Ian & Lahdelma, Risto & Salminen, Pekka, 2014. "The analytic hierarchy process with stochastic judgements," European Journal of Operational Research, Elsevier, vol. 238(2), pages 552-559.
    7. van Valkenhoef, Gert & Tervonen, Tommi, 2016. "Entropy-optimal weight constraint elicitation with additive multi-attribute utility models," Omega, Elsevier, vol. 64(C), pages 1-12.
    8. Durbach, Ian N., 2009. "The use of the SMAA acceptability index in descriptive decision analysis," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1229-1237, August.
    9. Durbach, Ian, 2009. "On the estimation of a satisficing model of choice using stochastic multicriteria acceptability analysis," Omega, Elsevier, vol. 37(3), pages 497-509, June.
    10. Wang, Haichao & Duanmu, Lin & Lahdelma, Risto & Li, Xiangli, 2017. "Developing a multicriteria decision support framework for CHP based combined district heating systems," Applied Energy, Elsevier, vol. 205(C), pages 345-368.

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