Towards a Classification of Route Selection Criteria for Route Planning Tools

2006 ◽  
pp. 481-492 ◽  
Author(s):  
Hartwig Hochmair
Keyword(s):  
Selection Criteria ◽  
Route Planning ◽  
Route Selection ◽  
Planning Tools

Towards a Multi Objective Path Optimisation for Car Navigation

2011 ◽  
Vol 65 (1) ◽  
pp. 125-144 ◽  
Author(s):  
Ching-Sheng Chiu ◽  
Chris Rizos
Keyword(s):  
Selection Criteria ◽  
Empirical Studies ◽  
Route Selection ◽  
Multi Objective ◽  
Optimal Paths ◽  
Proposed Model ◽  
Shortest Distance ◽  
Shortest Path Algorithms ◽  
Car Navigation System ◽  
Car Navigation

In a car navigation system the conventional information used to guide drivers in selecting their driving routes typically considers only one criterion, usually the Shortest Distance Path (SDP). However, drivers may apply multiple criteria to decide their driving routes. In this paper, possible route selection criteria together with a Multi Objective Path Optimisation (MOPO) model and algorithms for solving the MOPO problem are proposed. Three types of decision criteria were used to present the characteristics of the proposed model. They relate to the cumulative SDP, passed intersections (Least Node Path – LNP) and number of turns (Minimum Turn Path – MTP). A two-step technique which incorporates shortest path algorithms for solving the MOPO problem was tested. To demonstrate the advantage that the MOPO model provides drivers to assist in route selection, several empirical studies were conducted using two real road networks with different roadway types. With the aid of a Geographic Information System (GIS), drivers can easily and quickly obtain the optimal paths of the MOPO problem, despite the fact that these paths are highly complex and difficult to solve manually.

scholarly journals An Evolutionary Method for Combining Different Feature Selection Criteria in Microarray Data Classification

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Nicoletta Dessì ◽  
Barbara Pes
Keyword(s):  
Microarray Data ◽  
Selection Criteria ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Research Area ◽  
Svm Classifier ◽  
Ranking Methods ◽  
Wrapper Approach ◽  
Relevant Gene

The classification of cancers from gene expression profiles is a challenging research area in bioinformatics since the high dimensionality of microarray data results in irrelevant and redundant information that affects the performance of classification. This paper proposes using an evolutionary algorithm to select relevant gene subsets in order to further use them for the classification task. This is achieved by combining valuable results from different feature ranking methods into feature pools whose dimensionality is reduced by a wrapper approach involving a genetic algorithm and SVM classifier. Specifically, the GA explores the space defined by each feature pool looking for solutions that balance the size of the feature subsets and their classification accuracy. Experiments demonstrate that the proposed method provide good results in comparison to different state of art methods for the classification of microarray data.

scholarly journals MKJ and MSS Classification of Solar-Type Stars Within 100 Parsecs of the Sun: Preliminary Results

1985 ◽  
Vol 111 ◽  
pp. 407-410
Author(s):  
M. Fracassini ◽  
L. E. Pasinetti ◽  
M. Borella ◽  
A. Pasinetti
Keyword(s):  
Spectral Type ◽  
Selection Criteria ◽  
The Sun ◽  
Preliminary Results ◽  
Good Selection ◽  
Color Indices ◽  
Solar Type

A study of the distribution of spectral types of Solar Type Stars (STS) in the revised MKJ and MSS classifications is made on 3919 F8-K3 HD spectral-type stars brighter than mv=10. By means of the solar color indices U-B and B-V 697 STS were selected. The spectral types G3V and G5V have the highest percentages in MSS and MKJ, respectively, confirming statistically the results published by Keenan and Pitts (1980) and by Hardorp (1982). The distribution of the color indices U-B and B-V in the revised G2V spectral type shows that these are good selection criteria for STS and are in the range 0.06 ≤ U-B ≤ 0.10 and 0.58 ≤ B-V ≤ 0.65.

Cognitive load during route selection increases reliance on spatial heuristics

2018 ◽  
Vol 71 (5) ◽  
pp. 1045-1056 ◽  
Author(s):  
Tad T Brunyé ◽  
Shaina B Martis ◽  
Holly A Taylor
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Cognitive Load ◽  
Initial Segment ◽  
Memory Load ◽  
Route Planning ◽  
Task Demands ◽  
Route Selection ◽  
Working Memory Load ◽  
Southern Route

Planning routes from maps involves perceiving the symbolic environment, identifying alternate routes and applying explicit strategies and implicit heuristics to select an option. Two implicit heuristics have received considerable attention, the southern route preference and initial segment strategy. This study tested a prediction from decision-making theory that increasing cognitive load during route planning will increase reliance on these heuristics. In two experiments, participants planned routes while under conditions of minimal (0-back) or high (2-back) working memory load. In Experiment 1, we examined how memory load impacts the southern route heuristic. In Experiment 2, we examined how memory load impacts the initial segment heuristic. Results replicated earlier results demonstrating a southern route preference (Experiment 1) and initial segment strategy (Experiment 2) and further demonstrated that evidence for heuristic reliance is more likely under conditions of concurrent working memory load. Furthermore, the extent to which participants maintained efficient route selection latencies in the 2-back condition predicted the magnitude of this effect. Together, results demonstrate that working memory load increases the application of heuristics during spatial decision making, particularly when participants attempt to maintain quick decisions while managing concurrent task demands.

Agent Reasoning Transparency’s Effect on Operator Workload

2016 ◽  
Vol 60 (1) ◽  
pp. 249-253 ◽  
Author(s):  
Julia L. Wright ◽  
Jessie Y.C. Chen ◽  
Michael J. Barnes ◽  
Peter A. Hancock
Keyword(s):  
Route Planning ◽  
Selection Task ◽  
Route Selection ◽  
Workload Analysis ◽  
Ambiguous Information ◽  
Simulated Environment ◽  
Nasa Tlx ◽  
Performance Satisfaction ◽  
Transparency Condition ◽  
Operator Workload

We examined how varying the transparency of agent reasoning affected operator workload in a route selection task, and how the differing measures of workload compared in assessing and understanding cognitive workload. Participants guided a three-vehicle convoy safely through a simulated environment of which they had a limited amount of information, while maintaining communication with command and monitoring their surroundings for threats. The intelligent route-planning agent assessed potential threats and suggested changes to the convoy route as needed. Each participant was assigned to one of three agent reasoning transparency conditions. Contrary to our hypothesis, NASA-TLX Global workload measures indicated that workload decreased slightly as access to agent reasoning increased. However, psychophysical measures of workload disagreed with NASA-TLX global results. Comparison of individual NASA-TLX workload factors with the psychophysical measures indicated that performance satisfaction was highest in the intermediary transparency condition, and the addition of ambiguous information in the highest transparency condition increased effort and resulted in increased complacent behavior. Recommendations for future workload analysis are offered.

The classification of supplier selection criteria with respect to lean or agile manufacturing strategies

2017 ◽  
Vol 28 (2) ◽  
pp. 232-249 ◽  
Author(s):  
Mohamed El Mokadem
Keyword(s):  
Supplier Selection ◽  
Selection Criteria ◽  
Small Sample Size ◽  
Principal Component ◽  
Agile Manufacturing ◽  
Small Sample ◽  
Underlying Structure ◽  
Principal Component Factor Analysis ◽  
Content Type

Purpose The purpose of this paper is to investigate how manufacturing strategies could affect the supplier selection criteria used by business firms. Design/methodology/approach Survey strategy was used to empirically understand the research argument. First, principal component factor analysis was employed to validate the underlying structure of the supplier selection criteria. Then, simple regression analysis was employed to test the research hypotheses. Findings Organizations pursuing lean strategies will emphasize factors that improve their efficiency when selecting their suppliers, while organizations pursuing agile strategies will assert factors that improve their ability to respond to customer unique requirements when selecting their suppliers. Research limitations/implications This study provides new insight for researchers to understand the effect of manufacturing strategies on the classification of supplier selection criteria. However, the small sample size might limit the ability to generalize research findings. Further research is required to confirm the findings using a wider sample. Practical implications This research provides practitioners with useful insights into how to select their suppliers based on their manufacturing strategies. Originality/value This paper classifies supplier selection criteria into three distinct groups: lean, agile, and common capabilities. Lean capability refers to the list of criteria that are highly relevant in selecting suppliers for lean implementers. Agile capability refers to the list of criteria that are highly relevant in selecting suppliers for agile implementers. Finally, common capability refers to the list of criteria that have comparable relevance in selecting suppliers for both lean and agile implementers.

When Route Selection Meets a Hill: Route Planning With Terrain Change

2012 ◽  
Author(s):  
Qi Wang ◽  
Holly A. Taylor ◽  
Tad T. Brunye
Keyword(s):  
Route Planning ◽  
Route Selection

scholarly journals Are self-ligating brackets related to less formation of Streptococcus mutans colonies? A systematic review

2014 ◽  
Vol 19 (1) ◽  
pp. 60-68 ◽  
Author(s):  
Leonard Euler Andrade Gomes do Nascimento ◽  
Margareth Maria Gomes de Souza ◽  
Angela Rita Pontes Azevedo ◽  
Lucianne Cople Maia
Keyword(s):  
Systematic Review ◽  
Streptococcus Mutans ◽  
Selection Criteria ◽  
Search Strategy ◽  
Cochrane Central Register ◽  
Inclusion Criteria ◽  
Central Register ◽  
Data Collection And Analysis

OBJECTIVE: To verify, by means of a systematic review, whether the design of brackets (conventional or self-ligating) influences adhesion and formation of Streptococcus mutans colonies. METHODS: Search strategy: four databases (Cochrane Central Register of Controlled Trials, Ovid ALL EMB Reviews, PubMed and BIREME) were selected to search relevant articles covering the period from January 1965 to December 2012. Selection Criteria: in first consensus by reading the title and abstract. The full text was obtained from publications that met the inclusion criteria. Data collection and analysis: Two reviewers independently extracted data using the keywords: conventional, self-ligating, biofilm, Streptococcus mutans, and systematic review; and independently evaluated the quality of the studies. In case of divergence, the technique of consensus was adopted. RESULTS: The search strategy resulted in 1,401 articles. The classification of scientific relevance revealed the high quality of the 6 eligible articles of which outcomes were not unanimous in reporting not only the influence of the design of the brackets (conventional or self-ligating) over adhesion and formation of colonies of Streptococcus mutans, but also that other factors such as the quality of the bracket type, the level of individual oral hygiene, bonding and age may have greater influence. Statistical analysis was not feasible because of the heterogeneous methodological design. CONCLUSIONS: Within the limitations of this study, it was concluded that there is no evidence for a possible influence of the design of the brackets (conventional or self-ligating) over colony formation and adhesion of Streptococcus mutans.

scholarly journals Meteorological Navigation by Integrating Metocean Forecast Data and Ship Performance Models into an ECDIS-like e-Navigation Prototype Interface

2021 ◽  
Vol 9 (5) ◽  
pp. 502
Author(s):  
Andrea Orlandi ◽  
Andrea Cappugi ◽  
Riccardo Mari ◽  
Francesco Pasi ◽  
Alberto Ortolani
Keyword(s):  
Performance Indicators ◽  
Selection Process ◽  
Route Planning ◽  
Route Optimization ◽  
Prototype System ◽  
Route Selection ◽  
Complex Processes ◽  
Specific Performance ◽  
Forecast Data ◽  
Ship Performance

In the complex processes of route planning, voyage monitoring, and post-voyage analysis, a key element is the capability of merging metocean forecast data with the available knowledge of ship responses in the encountered environmental conditions. In this context, a prototype system has been implemented capable of integrating metocean models forecasts with ship specific performance data and models. The work is based on the exploitation of an open source ECDIS-like system originally developed in the e-Navigation framework. The resulting prototype system allows the uploading and visualization of metocean data, the consequent computation of fuel consumption along each analyzed route, and the evaluation of the encountered meteo-marine conditions on each route way point. This allows us to “effectively and deeply dig inside” the various layers of available metocean forecast data regarding atmospheric and marine conditions and evaluating their effects on ship performance indicators. The system could also be used to trigger route optimization algorithms and subsequently evaluate the results. All these functionalities are tailored in order to facilitate the “what-if” analysis in the route selection process performed by deck officers. Many of the added functionalities can be utilized also in a shore-based fleet monitoring and management center. A description is given of the modeling and visualization approaches that have been implemented. Their potentialities are illustrated through the discussion of some examples in Mediterranean navigation.

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