Bus Timetabling as a Fuzzy Multiobjective Optimization Problem Using Preference- Based Genetic Algorithm
نویسنده
چکیده
Transportation plays a vital role in the development of a country and the car is the most commonly used means. However, in third world countries long waiting time for public buses is a common problem, especially when people need to switch buses. The problem becomes critical when one considers buses joining different villages and cities. Theoretically this problem can be solved by assigning more buses on the route, which is not possible due to economical problem. Another option is to schedule the buses so that customers who want to switch buses at junction cities need not have to wait long. This paper discusses how to model single frequency routes bus timetabling as a fuzzy multiobjective optimization problem and how to solve it using preferencebased genetic algorithm by assigning appropriate fuzzy preference to the need of the customers. The idea will be elaborated with an example.
منابع مشابه
Optimal Power Flow With Four Conflicting Objective Functions Using Multiobjective Ant Lion Algorithm: A Case Study of the Algerian Electrical Network
In this study, a multiobjective optimization is applied to Optimal Power Flow Problem (OPF). To effectively achieve this goal, a Multiobjective Ant Lion algorithm (MOALO) is proposed to find the Pareto optimal front for the multiobjective OPF. The aim of this work is to reach good solutions of Active and Reactive OPF problem by optimizing 4-conflicting objective functions simultaneously. Here a...
متن کاملGenerating Optimal Timetabling for Lecturers using Hybrid Fuzzy and Clustering Algorithms
UCTTP is a NP-hard problem, which must be performed for each semester frequently. The major technique in the presented approach would be analyzing data to resolve uncertainties of lecturers’ preferences and constraints within a department in order to obtain a ranking for each lecturer based on their requirements within a department where it is attempted to increase their satisfaction and develo...
متن کاملInteractive Fuzzy Modeling by Evolutionary Multiobjective Optimization with User Preference
One of the new trends in genetic fuzzy systems (GFS) is the use of evolutionary multiobjective optimization (EMO) algorithms. This is because EMO algorithms can easily handle two conflicting objectives (i.e., accuracy maximization and complexity minimization) when we design accurate and compact fuzzy rule-based systems from numerical data. Since the main advantage of fuzzy rule-based systems co...
متن کاملUsing fuzzy c-means clustering algorithm for common lecturer timetabling among departments
University course timetabling problem is one of the hard problems and it must be done for each term frequently which is an exhausting and time consuming task. The main technique in the presented approach is focused on developing and making the process of timetabling common lecturers among different departments of a university scalable. The aim of this paper is to improve the satisfaction of com...
متن کاملFuzzy Mutated Evolutionary Programming Based Algorithm for Multi-Objective Reactive Power Optimization
This paper presents an efficient and simple approach for solving the Multiobjective reactive power optimization problem. Fuzzy Logic has been applied in combination with Evolutionary Programming (EP). In order to have a better convergence in EP the mutation process is incorporated with Fuzzy Logic which leads to an improved technique called as Fuzzy Mutated Evolutionary Programming (FMEP). The ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012