Required relationship between objective function and Pareto frontier orders - Practical implications

2001 ◽  
Author(s):  
Achille Messac ◽  
Amir Ismail-Yahaya
Keyword(s):  
Objective Function ◽  
Pareto Frontier ◽  
Practical Implications

scholarly journals Compensation and Weights for Trade-offs in Engineering Design: Beyond the Weighted Sum

2005 ◽  
Vol 127 (6) ◽  
pp. 1045-1055 ◽  
Author(s):  
Michael J. Scott ◽  
Erik K. Antonsson
Keyword(s):  
Objective Function ◽  
Engineering Design ◽  
Single Point ◽  
Pareto Frontier ◽  
Theoretical Interpretation ◽  
Pareto Optimum ◽  
Additional Parameter ◽  
Weighted Sum ◽  
Importance Weights ◽  
Trade Offs

Multicriteria decision support methods are common in engineering design. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. It has long been known that a weighted sum, when used for multicriteria optimization, may fail to locate all points on a nonconvex Pareto frontier. More recent results from the optimization literature relate the curvature of an objective function to its ability to capture Pareto points, but do not consider the significance of the objective function parameters in choosing one Pareto point over another. A parametrized family of aggregations appropriate for engineering design is shown to model decisions capturing all possible trade-offs, and therefore can direct the solution to any Pareto optimum. This paper gives a mathematical and theoretical interpretation of the parameters of this family of aggregations as defining a degree of compensation among criteria as well as a measure of their relative importance. The inability to reach all Pareto optima is shown to be surmounted by this consideration of degree of compensation as an additional parameter of the decision. Additionally, the direct specification of importance weights is common to many decision methods. The choice of a single point from a Pareto frontier by specifying importance weights alone is shown to depend on the degree of compensation implicit in the aggregation. Thus both the degree of compensation and weights must be considered to capture all potentially acceptable decisions. A simple truss design example is used here to illustrate the concepts.

Benchmarking the Performance of a Machine Learning Classifier Enabled Multiobjective Genetic Algorithm on Six Standard Test Functions

2017 ◽  
Author(s):  
Kayla Zeliff ◽  
Walter Bennette ◽  
Scott Ferguson
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Objective Function ◽  
Hybrid Approach ◽  
Pareto Frontier ◽  
Population Diversity ◽  
Benchmark Problems ◽  
Multiobjective Genetic Algorithm ◽  
Learning Classifier ◽  
Function Calls

Previous work tested a multi-objective genetic algorithm that was integrated with a machine learning classifier to reduce the number of objective function calls. Four machine learning classifiers and a baseline “No Classifier” option were evaluated. Using a machine learning classifier to create a hybrid multiobjective genetic algorithm reduced objective function calls by 75–85% depending on the classifier used. This work expands the analysis of algorithm performance by considering six standard benchmark problems from the literature. The problems are designed to test the ability of the algorithm to identify the Pareto frontier and maintain population diversity. Results indicate a tradeoff between the objectives of Pareto frontier identification and solution diversity. The “No Classifier” baseline multiobjective genetic algorithm produces the frontier with the closest proximity to the true frontier while a classifier option provides the greatest diversity when the number of generations is fixed. However, there is a significant reduction in computational expense as the number of objective function calls required is significantly reduced, highlighting the advantage of this hybrid approach.

scholarly journals Designing a bi-objective decision support model for the disaster management

2021 ◽  
Author(s):  
Sina Nayeri ◽  
Ebrahim Asadi-Gangraj ◽  
Saeed Emami ◽  
Javad Rezaeian
Keyword(s):  
Objective Function ◽  
Disaster Management ◽  
Performance Metrics ◽  
Pareto Frontier ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Test Problems ◽  
Decision Support Model ◽  
Nsga Ii ◽  
The Impact

This paper addresses the allocation and scheduling of the relief teams as one of the main issues in the response phase of the disaster management. In this study, a Bi-Objective Mixed Integer Programming (BOMIP) model is proposed to assign and schedule of the relief teams in the disasters. The first objective function aims to minimize the sum of weighted completion times of the incidents and the second objective function also minimizes the sum of weighted tardiness of the relief operations. In order to more similar to the real-world, time-windows for the incidents and damaged routes are considered in this research. Furthermore, the actual relief time of an incident by the relief team is calculated according to the position on the corresponding relief team and fatigue effect. Due to NP-hardness of the considered problem, the proposed model cannot present the optimal solution in the reasonable time. Thus, NSGA-II and PSO algorithms are applied to solve the problem. Furthermore, the obtained results of  the proposed algorithms are compared with respect to different performance metrics in large size test problems. Finally, in order to investigate the impact of some parameters on the Pareto frontier, the sensitivity analysis and the managerial suggestions are provided.

The Differential Effectiveness of the Cognitive Interview Instructions for Enhancing Witnesses’ Memory of a Familiar Event

2014 ◽  
Vol 73 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Magali Ginet ◽  
Jacques Py ◽  
Cindy Colomb
Keyword(s):  
Cognitive Interview ◽  
Critical Event ◽  
Surgical Operation ◽  
Differential Effectiveness ◽  
Correct Information ◽  
Control Instruction ◽  
The Individual ◽  
Practical Implications

This study examines the influence of familiarity on witnesses’ memory and the individual effectiveness of each of the four cognitive interview instructions in improving witnesses’ recall of scripted events. Participants (N = 195), either familiar or unfamiliar with the hospital script, were presented with a video of a surgical operation. One week later, an interviewer used one of the four cognitive interview instructions or a control instruction to ask them about the video. Participants familiar with the surgery context recalled significantly more correct information and, in particular, more consistent and irrelevant details than those unfamiliar with the surgery context. Furthermore, the results confirmed the effectiveness of all four cognitive interview mnemonics in enhancing the amount of correct information reported, irrespective of the participants’ familiarity with the critical event. However, their efficacy differed depending on the category of details considered. The practical implications of these results are discussed.

How Do People Share Their Positive Events?

2016 ◽  
Vol 37 (4) ◽  
pp. 250-259 ◽  
Author(s):  
Cara A. Palmer ◽  
Meagan A. Ramsey ◽  
Jennifer N. Morey ◽  
Amy L. Gentzler
Keyword(s):  
Cluster Analysis ◽  
Communication Technology ◽  
Big Five ◽  
Well Being ◽  
Big Five Personality Traits ◽  
Big Five Personality ◽  
Positive Events ◽  
Growing Body ◽  
Sharing Patterns ◽  
Practical Implications

Abstract. Research suggests that sharing positive events with others is beneficial for well-being, yet little is known about how positive events are shared with others and who is most likely to share their positive events. The current study expanded on previous research by investigating how positive events are shared and individual differences in how people share these events. Participants (N = 251) reported on their likelihood to share positive events in three ways: capitalizing (sharing with close others), bragging (sharing with someone who may become jealous or upset), and mass-sharing (sharing with many people at once using communication technology) across a range of positive scenarios. Using cluster analysis, five meaningful profiles of sharing patterns emerged. These profiles were associated with gender, Big Five personality traits, narcissism, and empathy. Individuals who tended to brag when they shared their positive events were more likely to be men, reported less agreeableness, less conscientiousness, and less empathy, whereas those who tended to brag and mass-share reported the highest levels of narcissism. These results have important theoretical and practical implications for the growing body of research on sharing positive events.

Cross-Lagged Relationships Between Self-Esteem, Self-Construal, and Happiness in a Three-Wave Longitudinal Study

2019 ◽  
Vol 40 (3) ◽  
pp. 177-185
Author(s):  
Daniela Moza ◽  
Laurențiu Maricuțoiu ◽  
Alin Gavreliuc
Keyword(s):  
Structural Equation ◽  
Time Lag ◽  
Self Esteem ◽  
Equation Modeling ◽  
Future Research ◽  
Cross Sectional ◽  
Self Construal ◽  
Self Worth ◽  
Practical Implications ◽  
Independent Person

Abstract. Previous research established that an independent construal of the self is associated with higher self-esteem, which, in turn, is associated with increased happiness. Regarding the directionality of these relationships, theoretical arguments have suggested that self-construal precedes self-esteem and that self-esteem precedes happiness. However, most research in this area is cross-sectional, thus limiting any conclusions about directionality. The present study tested these relationships in 101 Romanian undergraduates using a 3-wave cross-lagged design with a 6-month time lag between every two waves. Structural equation modeling analyses revealed that self-esteem is an antecedent of both happiness and dimensions of independent self-construal (i.e., consistency vs. variability and self-expression vs. harmony). In other words, one’s positive evaluation of self-worth precedes one’s self-perception as being a happy and independent person. The findings are discussed with respect to the theoretical and practical implications, along with limitations and suggestions for future research.

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