Transportation optimization with fuzzy trapezoidal numbers based on possibility theory

Dayi He; Ran Li; Qi Huang; Ping Lei

doi:10.1371/journal.pone.0105142

Transportation optimization with fuzzy trapezoidal numbers based on possibility theory

PLoS One. 2014 Aug 19;9(8):e105142. doi: 10.1371/journal.pone.0105142. eCollection 2014.

Authors

Dayi He¹, Ran Li¹, Qi Huang¹, Ping Lei¹

Affiliation

¹ School of Humanities & Economic Management, Lab of Resources & Environment Management, China University of Geosciences (Beijing), Beijing, P. R. China.

Abstract

In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are assumed to be fuzzy trapezoidal numbers. Based on possibility theory and consistent with decision-makers' subjectiveness and practical requirements, the fuzzy transportation problem is transformed to a crisp linear transportation problem by defuzzifying fuzzy constraints and objectives with application of fractile and modality approach. Finally, a numerical example is provided to exemplify the application of fuzzy transportation programming and to verify the validity of the proposed methods.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Fuzzy Logic
Humans
Models, Theoretical
Transportation*
Uncertainty

Grants and funding

This research is supported by the Fundamental Research Funds for the Central Universities (2-9-2012-86) and supported by Key Laboratory of Carrying Capacity Assessment for Resource and Environment, MLR (CCA2012.05). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.