scholarly journals GENETIC ALGORITHM FOR SOLVING DYNAMIC SIMULTANEOUS ROUTE AND DEPARTURE TIME EQUILIBRIUM PROBLEM

Transport ◽  
2008 ◽  
Vol 23 (1) ◽  
pp. 73-77 ◽  
Author(s):  
Shu-Guang Li
Keyword(s):  
Genetic Algorithm ◽  
Equilibrium Problem ◽  
Departure Time ◽  
Flow Conservation

We present a genetic algorithm for solving dynamic simultaneous route and departure time equilibrium problem. Not only can a flow‐swapping process in the algorithm guarantee the flow conservation constraints between OD pair, but also accelerate the convergence velocity of the algorithm. Finally, a simulation example shows feasibility and validity of genetic algorithm.

scholarly journals Distribution Optimization Model for Passenger Departure via Multimodal Transit

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Yuchuan Du ◽  
Shanchuan Yu ◽  
Shengchuan Jiang ◽  
Yuxiong Ji
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Transportation Network ◽  
Departure Time ◽  
Optimized Distribution ◽  
In Transit

International airports in China have become a complex hub between airport and multimodal transit stations. Dissimilar passenger departure demands in different transit mode cause wide gaps among departure times from airport to these modes. In this context, hub managers need to balance the distribution of air passengers to transit modes in order to reduce departure delays and alleviate the congestion in transit stations, even though they cannot change the operating plan of airport or transit stations. However, few research efforts have addressed this distribution. Therefore, we developed a distribution optimization model for passenger departure that minimizes the average departure time and is solved by Genetic Algorithm. To describe differences in passenger choices, without taking into consideration the metropolitan transportation network outside the airport, we introduced the concept of rigid and elastic departures. To reflect the tendency of elastic passengers to choose different transit modes, we assume that the passengers change to other modes in different proportions. A case revealed that the presence of rigid passengers allows managers to partly balance the distribution of passengers and improve the average departure time. When the volume of passengers approaches the peak volume, the optimized distribution significantly improves the departure time.

The Industry Assembly Line Layout’s Modeling and Simulation in Industry Manufacturing Based on Genetic Algorithm

2013 ◽  
Vol 675 ◽  
pp. 3-7
Author(s):  
Fang Guo ◽  
Zhi Hong Huang
Keyword(s):  
Genetic Algorithm ◽  
Modeling And Simulation ◽  
Equilibrium Problem ◽  
Assembly Line ◽  
Simulation Software ◽  
Heuristic Procedure ◽  
Plant Simulation ◽  
Line Design

The equilibrium problem is one important aspect of industry assembly line design. This paper puts forward the method to solve the industry assembly line’s equilibrium problem based on the genetic algorithm’s heuristic procedure and on this basis it also optimizes the industry assembly line’s layout and synthetically considers the material carrying cost, plant area’s use ratio and other factors in industry manufacturing. Then it optimizes by eM-Plant simulation software and combining with genetic algorithm to efficiently acquire visual and satisfying layout effects. At last, it uses examples of industry assembly line to verify this method’s feasibility.

Trasfugen: Traffic assignment of urban network by an approximation fuzzy genetic algorithm

2018 ◽  
Vol 09 (04) ◽  
pp. 1850034 ◽  
Author(s):  
Mahdi Kherad ◽  
Hamed Vahdat-Nejad ◽  
Morteza Araghi
Keyword(s):  
Genetic Algorithm ◽  
Approximation Algorithm ◽  
Equilibrium Problem ◽  
Time Complexity ◽  
Traffic Assignment ◽  
User Equilibrium ◽  
Deterministic Algorithm ◽  
Urban Network ◽  
Assignment Method ◽  
Fuzzy Genetic

This paper proposes the Trasfugen method for traffic assignment aimed at solving the user equilibrium problem. To this end, the method makes use of a genetic algorithm. A fuzzy system is proposed for controlling the mutation and crossover rates of the genetic algorithm, and the corrective strategy is exploited for handling the equilibrium problem constraints. In the model, an approximation algorithm is proposed for obtaining the paths between the origin–destination pairs in the demand matrix. Unlike the traditional deterministic algorithm that has exponential time complexity, this approximation algorithm has polynomial time complexity and is executed much faster. Afterward, the Trasfugen method is applied to the urban network of Tehran metropolitan and the efficiency is investigated. Upon comparing the results obtained from the proposed model with those obtained from the conventional traffic assignment method, namely, the Frank–Wolfe method; it is shown that the proposed algorithm, while acting worse during the initial iterations, achieves better results in the subsequent iterations. Moreover, it prevents the occurrence of local optimal points as well as early/premature convergence, thus producing better results than the Frank–Wolfe algorithm.

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
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