Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
TSP Race: Minimizing completion time in time-sensitive applications
Date
2015-07-01
Author
Çavdar, Bahar
Sokol, Joel
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
190
views
0
downloads
Cite This
In this paper, we present an approach for parallelizing computation and implementation time for problems where the objective is to complete the solution as soon after receiving the problem instance as possible. We demonstrate the approach on the TSP. We define the TSP race problem, present a computation-implementation parallelized (CIP) approach for solving it, and demonstrate CIP's effectiveness on TSP Race instances. We also demonstrate a method for determining a priori when CIP will be effective. Although in this paper we focus on TSP, our general CIP approach can be effective on other problems and applications with similar time sensitivity.
Subject Keywords
Computation-implementation parallelization
,
TSP race
,
TSP
,
Heuristic
URI
https://hdl.handle.net/11511/57128
Journal
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
DOI
https://doi.org/10.1016/j.ejor.2014.12.022
Collections
Department of Industrial Engineering, Article
Suggestions
OpenMETU
Core
Multi-objective integer programming: A general approach for generating all non-dominated solutions
Oezlen, Melih; Azizoğlu, Meral (Elsevier BV, 2009-11-16)
In this paper we develop a general approach to generate all non-dominated solutions of the multi-objective integer programming (MOIP) Problem. Our approach, which is based on the identification of objective efficiency ranges, is an improvement over classical epsilon-constraint method. Objective efficiency ranges are identified by solving simpler MOIP problems with fewer objectives. We first provide the classical epsilon-constraint method on the bi-objective integer programming problem for the sake of comple...
Feedback motion planning of unmanned underwater vehicles via random sequential composition
Ege, Emr; Orguner, Umut; Department of Electrical and Electronics Engineering (2019)
In this thesis, we propose a new motion planning method to robustly and computationally efficiently solve (probabilistic) coverage, path planning, and navigation problems for unmanned underwater vehicles (UUVs). Our approach is based on synthesizing two existing methodologies: sequential decomposition of dynamic behaviors and rapidly exploring random trees. The main motivation for this integrated solution is a robust feed-back based and computationally feasible motion planning and navigation algorithm that ...
Continuous optimization approaches for clustering via minimum sum of squares
Akteke-Ozturk, Basak; Weber, Gerhard Wilhelm; Kropat, Erik (2008-05-23)
In this paper, we survey the usage of semidefinite programming (SDP), and nonsmooth optimization approaches for solving the minimum sum of squares problem which is of fundamental importance in clustering. We point out that the main clustering idea of support vector clustering (SVC) method could be interpreted as a minimum sum of squares problem and explain the derivation of semidefinite programming and a nonsmooth optimization formulation for the minimum sum of squares problem. We compare the numerical resu...
Residual based Adaptive Unscented Kalman filter for satellite attitude estimation
Söken, Halil Ersin (2012-12-01)
Determining the process noise covariance matrix in Kalman filtering applications is a difficult task especially for estimation problems of the high-dimensional states where states like biases or system parameters are included. This study introduces a simplistic residual based adaptation method for the Unscented Kalman Filter (UKF), which is used for small satellite attitude estimation. For a satellite with gyros and magnetometers onboard, the proposed adaptive UKF algorithm estimates the attitude as well as...
Signaling Games for Log-Concave Distributions: Number of Bins and Properties of Equilibria
Kazikli, Ertan; Sarıtaş, Serkan; GEZİCİ, Sinan; Linder, Tamas; Yuksel, Serdar (2022-03-01)
We investigate the equilibrium behavior for the decentralized cheap talk problem for real random variables and quadratic cost criteria in which an encoder and a decoder have misaligned objective functions. In prior work, it has been shown that the number of bins in any equilibrium has to be countable, generalizing a classical result due to Crawford and Sobel who considered sources with density supported on [0, 1]. In this paper, we first refine this result in the context of log-concave sources. For sources ...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Çavdar and J. Sokol, “TSP Race: Minimizing completion time in time-sensitive applications,”
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
, pp. 47–54, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57128.