AN EFFICIENT AND PRACTICALLY ROBUST HYBRID METAHEURISTIC ALGORITHM FOR SOLVING FUZZY BUS TERMINAL LOCATION PROBLEMS

2012 ◽  
Vol 29 (02) ◽  
pp. 1250009 ◽  
Author(s):  
SAMAN BABAIE-KAFAKI ◽  
REZA GHANBARI ◽  
NEZAM MAHDAVI-AMIRI
Keyword(s):  
Public Transportation ◽  
Hybrid Algorithm ◽  
Large Scale ◽  
Optimal Solution ◽  
Neighborhood Search ◽  
Test Problems ◽  
Nonparametric Statistical Test ◽  
Scale Test ◽  
Nonparametric Statistical ◽  
Fuzzy Parameters

Bus network design is an important problem in public transportation. In practice, some parameters of this problem are uncertain. We propose two models for the bus terminal location problem with fuzzy parameters. In the first formulation, the number of passengers corresponding to each node is a fuzzy number. In the second formulation, an additional assumption of fuzzy neighborhood is considered. These problems being NP-hard, we use a genetic algorithm (GA) and a simulated annealing (SA) algorithm for solving them. We also propose an idea to hybridize these algorithms. In our hybrid algorithm, SA is applied as a neighborhood search procedure of GA on the best individual of the population, which is the best available approximation of the optimal solution, with a varying probability that is gradually increased with the increase in the number of iterations in GA. We then implement GA, SA, our hybrid algorithm, and a recently proposed hybrid algorithm making use of a constant probability for application of SA on all the individuals of the population of GA, and use a nonparametric statistical test to compare their performances on a collection of randomly generated medium to large-scale test problems. Results of computational experiments demonstrating the efficiency and practicability of our proposed algorithm are reported.

scholarly journals Modified Conjugate Gradient Method via DFP Update for Solving Systems of Nonlinear Equations

2020 ◽  
Vol 3 (1) ◽  
pp. 43-49
Author(s):  
M K Dauda
Keyword(s):  
Large Scale ◽  
Memory Storage ◽  
Systems Of Nonlinear Equations ◽  
Test Problems ◽  
Systems Of Equations ◽  
Nonlinear Systems Of Equations ◽  
Derivative Free ◽  
Scale Test ◽  
Derivative Free Method ◽  
Modified Conjugate Gradient Method

In this study, a fully derivative-free method for solving large scale nonlinear systems of equations via memoryless DFP update is presented. The new proposed method is an enhanced DFP (Davidon-FletcherPowell) update which is matrix and derivative free thereby require low memory storage. Under suitable conditions, the proposed method converges globally. Numerical comparisons using a set of large-scale test problems showed that the proposed method is efficient.

scholarly journals Hybridization of Adaptive Differential Evolution with an Expensive Local Search Method

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Rashida Adeeb Khanum ◽  
Muhammad Asif Jan ◽  
Nasser Mansoor Tairan ◽  
Wali Khan Mashwani
Keyword(s):  
Global Optimization ◽  
Local Search ◽  
Differential Evolution ◽  
Large Scale ◽  
Optimization Problems ◽  
Neighborhood Search ◽  
Test Problems ◽  
Adaptive Differential Evolution ◽  
External Archive ◽  
Search Capability

Differential evolution (DE) is an effective and efficient heuristic for global optimization problems. However, it faces difficulty in exploiting the local region around the approximate solution. To handle this issue, local search (LS) techniques could be hybridized with DE to improve its local search capability. In this work, we hybridize an updated version of DE, adaptive differential evolution with optional external archive (JADE) with an expensive LS method, Broydon-Fletcher-Goldfarb-Shano (BFGS) for solving continuous unconstrained global optimization problems. The new hybrid algorithm is denoted by DEELS. To validate the performance of DEELS, we carried out extensive experiments on well known test problems suits, CEC2005 and CEC2010. The experimental results, in terms of function error values, success rate, and some other statistics, are compared with some of the state-of-the-art algorithms, self-adaptive control parameters in differential evolution (jDE), sequential DE enhanced by neighborhood search for large-scale global optimization (SDENS), and differential ant-stigmergy algorithm (DASA). These comparisons reveal that DEELS outperforms jDE and SDENS except DASA on the majority of test instances.

scholarly journals A Hybrid Estimation of Distribution Algorithm and Nelder-Mead Simplex Method for Solving a Class of Nonlinear Bilevel Programming Problems

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Aihong Ren ◽  
Yuping Wang ◽  
Fei Jia
Keyword(s):  
Bilevel Programming ◽  
Simplex Method ◽  
Hybrid Algorithm ◽  
Fitness Function ◽  
Optimal Solution ◽  
Estimation Of Distribution Algorithm ◽  
Test Problems ◽  
Estimation Of Distribution ◽  
Bilevel Programming Problems ◽  
Level Variable

We propose a hybrid algorithm based on estimation of distribution algorithm (EDA) and Nelder-Mead simplex method (NM) to solve a class of nonlinear bilevel programming problems where the follower’s problem is linear with respect to the lower level variable. The bilevel programming is an NP-hard optimization problem, for which EDA-NM is applied as a new tool aiming at obtaining global optimal solutions of such a problem. In fact, EDA-NM is very easy to be implementedsince it does not require gradients information. Moreover, the hybrid algorithm intends to produce faster and more accurate convergence. In the proposed approach, for fixed upper level variable, we make use of the optimality conditions of linear programming to deal with the follower’s problem and obtain its optimal solution. Further, the leader’s objective function is taken as the fitness function. Based on these schemes, the hybrid algorithm is designed by combining EDA with NM. To verify the performance of EDA-NM, simulations on some test problems are made, and the results demonstrate that the proposed algorithm has a better performance than the compared algorithms. Finally, the proposed approach is used to solve a practical example about pollution charges problem.

scholarly journals A study of different metaheuristics to solve the urban transit crew scheduling problem

2014 ◽  
Vol 8 (4) ◽  
pp. 227-251 ◽  
Author(s):  
Gustavo Peixoto Silva ◽  
Allexandre Fortes da Silva Reis
Keyword(s):  
Local Search ◽  
Public Transportation ◽  
Large Scale ◽  
Classical Method ◽  
Real Data ◽  
Crew Scheduling ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Belo Horizonte ◽  
Crew Scheduling Problem

This paper explores different local search methods associated with the metaheuristic Iterated Local Search (ILS) to solve the Crew Scheduling Problem (CSP) of a Public Transportation System. The results from ILS were compared to those obtained in a previous work from the same authors that used the Variable Neighborhood Search (VNS). Initially, both metaheuristics were implemented using, as local search, the classical First Improvement Method, performing "guided" reallocation and exchange of crew tasks. The guided reallocation/exchange replaces random components from the classical method by searching the best position to insert the task. Further, the Very Large-scale Neighborhood Search (VLNS) technique was used as a local search procedure in the metaheuristics. This technique has substantially more neighbors than the 2-opt neighborhoods, since it performs a chain exchange of tasks from different crews. Both versions of metaheuristics were applied to a set of real data from a company operating in the city of Belo Horizonte, producing more economical schedules than those adopted by the company. The results are presented and discussed in this work.

scholarly journals Efficient matrix-free direction method with line search for solving large-scale system of nonlinear equations

2020 ◽  
Vol 30 (4) ◽  
pp. 399-412
Author(s):  
Abubakar Halilu ◽  
Mohammed Waziri ◽  
Ibrahim Yusuf
Keyword(s):  
Nonlinear Equations ◽  
Large Scale ◽  
Line Search ◽  
Test Problems ◽  
System Of Nonlinear Equations ◽  
Inexact Line Search ◽  
Large Scale Problems ◽  
Scale Test ◽  
Line Search Technique ◽  
Matrix Free

We proposed a matrix-free direction with an inexact line search technique to solve system of nonlinear equations by using double direction approach. In this article, we approximated the Jacobian matrix by appropriately constructed matrix-free method via acceleration parameter. The global convergence of our method is established under mild conditions. Numerical comparisons reported in this paper are based on a set of large-scale test problems and show that the proposed method is efficient for large-scale problems.

Age Advantages of Emotional Experience during the COVID-19 Pandemic are Robust, but Diminished Compared to Pre-pandemic Conditions

2020 ◽  
Author(s):  
Rui Sun ◽  
Disa Sauter
Keyword(s):  
Older Adults ◽  
Large Scale ◽  
Negative Emotion ◽  
Emotional Experience ◽  
Negative Emotions ◽  
Older Individuals ◽  
Selection Strategies ◽  
Scale Test ◽  
Prolonged Stress

Getting old is generally seen as unappealing, yet aging confers considerable advantages in several psychological domains (North & Fiske, 2015). In particular, older adults are better off emotionally than younger adults, with aging associated with the so-called “age advantages,” that is, more positive and less negative emotional experiences (Carstensen et al., 2011). Although the age advantages are well established, it is less clear whether they occur under conditions of prolonged stress. In a recent study, Carstensen et al (2020) demonstrated that the age advantages persist during the COVID-19 pandemic, suggesting that older adults are able to utilise cognitive and behavioural strategies to ameliorate even sustained stress. Here, we build on Carstensen and colleagues’ work with two studies. In Study 1, we provide a large-scale test of the robustness of Carstensen and colleagues’ finding that older individuals experience more positive and less negative emotions during the COVID-19 pandemic. We measured positive and negative emotions along with age information in 23,629 participants in 63 countries in April-May 2020. In Study 2, we provide a comparison of the age advantages using representative samples collected before and during the COVID-19 pandemic. We demonstrate that older people experience less negative emotion than younger people during the prolonged stress of the COVID-19 pandemic. However, the advantage of older adults was diminished during the pandemic, pointing to a likely role of older adults use of situation selection strategies (Charles, 2010).

scholarly journals GNSS RUMS: GNSS Realistic Urban Multiagent Simulator for Collaborative Positioning Research

2021 ◽  
Vol 13 (4) ◽  
pp. 544
Author(s):  
Guohao Zhang ◽  
Bing Xu ◽  
Hoi-Fung Ng ◽  
Li-Ta Hsu
Keyword(s):  
Urban Area ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Large Scale ◽  
Transportation Systems ◽  
Accurate Localization ◽  
Gnss Receivers ◽  
Multipath Signal ◽  
Scale Test ◽  
Error Behavior

Accurate localization of road agents (GNSS receivers) is the basis of intelligent transportation systems, which is still difficult to achieve for GNSS positioning in urban areas due to the signal interferences from buildings. Various collaborative positioning techniques were recently developed to improve the positioning performance by the aid from neighboring agents. However, it is still challenging to study their performances comprehensively. The GNSS measurement error behavior is complicated in urban areas and unable to be represented by naive models. On the other hand, real experiments requiring numbers of devices are difficult to conduct, especially for a large-scale test. Therefore, a GNSS realistic urban measurement simulator is developed to provide measurements for collaborative positioning studies. The proposed simulator employs a ray-tracing technique searching for all possible interferences in the urban area. Then, it categorizes them into direct, reflected, diffracted, and multipath signal to simulate the pseudorange, C/N0, and Doppler shift measurements correspondingly. The performance of the proposed simulator is validated through real experimental comparisons with different scenarios based on commercial-grade receivers. The proposed simulator is also applied with different positioning algorithms, which verifies it is sophisticated enough for the collaborative positioning studies in the urban area.

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