scholarly journals Addressing the Bike Repositioning Problem in Bike Sharing System: A Two-Stage Stochastic Programming Model

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qiong Tang ◽  
Zhuo Fu ◽  
Dezhi Zhang ◽  
Hao Guo ◽  
Minyi Li
Keyword(s):  
Stochastic Programming ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Two Stage ◽  
System A ◽  
Penalty Costs ◽  
Bike Sharing ◽  
Holding Cost ◽  
Stochastic Programming Model ◽  
Annealing Algorithm

In this paper, a bike repositioning problem with stochastic demand is studied. The problem is formulated as a two-stage stochastic programming model to optimize the routing and loading/unloading decisions of the repositioning truck at each station and depot under stochastic demands. The goal of the model is to minimize the expected total sum of the transportation costs, the expected penalty costs at all stations, and the holding cost of the depot. A simulated annealing algorithm is developed to solve the model. Numerical experiments are conducted on a set of instances from 20 to 90 stations to demonstrate the effectiveness of the solution algorithm and the accuracy of the proposed two-stage stochastic model.

An interval-fuzzy two-stage stochastic programming method for filter management of hydraulic systems

2014 ◽  
Vol 229 (15) ◽  
pp. 2788-2809
Author(s):  
Hui Ji ◽  
Songlin Nie ◽  
Yeqing Huang
Keyword(s):  
Stochastic Programming ◽  
Hydraulic System ◽  
Programming Model ◽  
Optimal Strategies ◽  
Management Policy ◽  
Continuous Variables ◽  
Hydraulic Systems ◽  
Two Stage ◽  
Interval Numbers ◽  
Stochastic Programming Model

An interval-fuzzy two-stage stochastic programming model for filter management of hydraulic system under uncertainties is proposed in this paper. The interval-fuzzy two-stage stochastic programming model integrates the two-stage stochastic programming, fuzzy programming, and interval parameter nonlinear programming into an optimization model of contamination control in hydraulic system. For a typical hydraulic system, it can be used for expressing the uncertainties existed in the purchase cost of filters, contamination ingression and generation rates, and contamination-holding capacity as probability functions, interval numbers, and fuzzy sets. The developed method is applied to examining the decisions on the adoption of bypass filter and selection of filters within multi-segments, multi-period, and multi-option context. All potential scenarios of filters management policy associated with different economic penalties, objectives, and reliability of system are analyzed. The results of the illustrative example show that the reasonable solutions are generated, including binary and continuous variables which help the decision maker identify optimal strategies for filter allocation and selection, planning the adoption of bypass filter under different working conditions.

A two-stage chance-constrained stochastic programming model for a bio-fuel supply chain network

2018 ◽  
Vol 195 ◽  
pp. 27-44 ◽  
Author(s):  
Md Abdul Quddus ◽  
Sudipta Chowdhury ◽  
Mohammad Marufuzzaman ◽  
Fei Yu ◽  
Linkan Bian
Keyword(s):  
Supply Chain ◽  
Stochastic Programming ◽  
Programming Model ◽  
Supply Chain Network ◽  
Two Stage ◽  
Fuel Supply ◽  
Stochastic Programming Model
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