scholarly journals Emergency Vehicle Dispatching and Redistribution in Highway Network Based on Bilevel Programming

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaohong Duan ◽  
Shouxin Song ◽  
Jiandong Zhao
Keyword(s):  
Bilevel Programming ◽  
Programming Model ◽  
Time Windows ◽  
Emergency Vehicle ◽  
Shuffled Frog Leaping Algorithm ◽  
Coverage Area ◽  
Vehicle Dispatching ◽  
Emergency Vehicles ◽  
Shuffled Frog Leaping ◽  
Bilevel Programming Model

Response time is a key factor in the emergency vehicle dispatching problem. Because regional emergency vehicles are limited, vehicle gaps will be created in the rescue station after vehicles are dispatched to several accidents, which affects quick response to the subsequent incidents. To solve this problem, a bilevel programming model for emergency vehicle dispatching and redistribution is established, of which the optimal objectives are the shortest rescue time for current accidents and the shortest time for vehicle redistribution, and the key constraints are emergency vehicle requirements and accident time windows. In the precondition of effective rescue of current accidents, emergency vehicles are redistributed according to the potential risks in the rescue station coverage area. A bilevel shuffled frog leaping algorithm is proposed to solve the bilevel programming model. The dispatching results of examples show that the model conforms to dispatching decision rule and the bilevel shuffled frog leaping algorithm can resolve the bilevel programming model fast and efficiently.

scholarly journals An Improved Shuffled Frog Leaping Algorithm and Its Application in Dynamic Emergency Vehicle Dispatching

2018 ◽  
Vol 2018 ◽  
pp. 1-34 ◽  
Author(s):  
Xiaohong Duan ◽  
Tianyong Niu ◽  
Qi Huang
Keyword(s):  
Real Time ◽  
Prediction Error ◽  
Travel Speed ◽  
Time Dependent ◽  
Emergency Vehicle ◽  
Shuffled Frog Leaping Algorithm ◽  
The Real ◽  
Vehicle Dispatching ◽  
Selection Strategies ◽  
Shuffled Frog Leaping

The traditional method for solving the dynamic emergency vehicle dispatching problem can only get a local optimal strategy in each horizon. In order to obtain the dispatching strategy that can better respond to changes in road conditions during the whole dispatching process, the real-time and time-dependent link travel speeds are fused, and a time-dependent polygonal-shaped link travel speed function is set up to simulate the predictable changes in road conditions. Response times, accident severity, and accident time windows are taken as key factors to build an emergency vehicle dispatching model integrating dynamic emergency vehicle routing and selection. For the unpredictable changes in road conditions caused by accidents, the dispatching strategy is adjusted based on the real-time link travel speed. In order to solve the dynamic emergency vehicle dispatching model, an improved shuffled frog leaping algorithm (ISFLA) is proposed. The global search of the improved algorithm uses the probability model of estimation of distribution algorithm to avoid the partial optimal solution. Based on the Beijing expressway network, the efficacy of the model and the improved algorithm were tested from three aspects. The results have shown the following: (1) Compared with SFLA, the optimization performance of ISFLA is getting better and better with the increase of the number of decision variables. When the possible emergency vehicle selection strategies are 815, the objective function value of optimal selection strategies obtained by the base algorithm is 210.10% larger than that of ISFLA. (2) The prediction error of the travel speed affects the accuracy of the initial emergency vehicle dispatching. The prediction error of ±10 can basically meet the requirements of the initial dispatching. (3) The adjustment of emergency vehicle dispatching strategy can successfully bypassed road sections affected by accidents and shorten the response time.

scholarly journals A Simultaneous Solution for Reserve Capacity Maximization and Delay Minimization Problems in Signalized Road Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Ozgur Baskan ◽  
Huseyin Ceylan ◽  
Cenk Ozan
Keyword(s):  
Bilevel Programming ◽  
Road Network ◽  
Programming Model ◽  
Numerical Test ◽  
User Equilibrium ◽  
Reserve Capacity ◽  
Delay Minimization ◽  
Weighted Sum Method ◽  
Capacity Maximization ◽  
Bilevel Programming Model

In this study, we present a bilevel programming model in which upper level is defined as a biobjective problem and the lower level is considered as a stochastic user equilibrium assignment problem. It is clear that the biobjective problem has two objectives: the first maximizes the reserve capacity whereas the second minimizes performance index of a road network. We use a weighted-sum method to determine the Pareto optimal solutions of the biobjective problem by applying normalization approach for making the objective functions dimensionless. Following, a differential evolution based heuristic solution algorithm is introduced to overcome the problem presented by use of biobjective bilevel programming model. The first numerical test is conducted on two-junction network in order to represent the effect of the weighting on the solution of combined reserve capacity maximization and delay minimization problem. Allsop & Charlesworth’s network, which is a widely preferred road network in the literature, is selected for the second numerical application in order to present the applicability of the proposed model on a medium-sized signalized road network. Results support authorities who should usually make a choice between two conflicting issues, namely, reserve capacity maximization and delay minimization.

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