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A nonlinear model for a capacitated random transportation network

Shiripour, S ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1080/21681015.2015.1078419
  3. Publisher: Taylor and Francis Ltd , 2015
  4. Abstract:
  5. In this study, we consider a capacitated location–multi-allocation–routing problem with population-dependent random travel times. The objective is to find appropriate locations as server locations among the candidate locations, allocate the existing population in each demand node to server locations, and determine the movement path of each member to reach its corresponding server with respect to the simultaneous change of the random travel times so that the expected total transportation time is minimized. In our study, the concept of population-dependent random travel times incurs two issues: (1) consideration of some random factors in computing the travel times and (2) impact of the traveling population (presence of people or vehicles) on these random factors simultaneously. Here, three random factors of the time spent in traffic, the number of accidents, and the number of road failures are considered. Also, the capacities of server nodes for servicing the people or vehicles and the capacities of arcs to pass the people or vehicles are assumed to be limited. Defining a linear function for population-dependent random travel time, we formulate the problem as a mixed-integer nonlinear programming model. Also, to investigate the validation and behavior of the proposed random model, several network examples are provided and computational results are analyzed
  6. Keywords:
  7. Poisson distribution function ; Crashworthiness ; Distribution functions ; Integer programming ; Location ; Nonlinear programming ; Poisson distribution ; Vehicles ; Capacitated location ; Computational results ; Mixed integer nonlinear programming models ; Mixed-integer nonlinear programming ; multi-allocation ; population-dependent random travel times ; Transportation network ; Transportation time ; Travel time
  8. Source: Journal of Industrial and Production Engineering ; Oct , 2015 , Page 500-515 ; 21681015 (ISSN)
  9. URL: http://www.tandfonline.com/doi/abs/10.1080/21681015.2015.1078419