Efficient Computation of Probabilistic Dominance in Multi-objective Optimization

Real-world problems typically require the simultaneous optimization of multiple, often conflicting objectives. Many of these multi-objective optimization problems are characterized by wide ranges of uncertainties in their decision variables or objective functions. To cope with such uncertainties, stochastic and robust optimization techniques are widely studied aiming to distinguish candidate solutions with uncertain objectives specified by confidence intervals, probability distributions, sampled data, or uncertainty sets. In this scope, this article first introduces a novel empirical approach for the comparison of candidate solutions with uncertain objectives that can follow arbitrary distributions. The comparison is performed through accurate and efficient calculations of the probability that one solution dominates the other in terms of each uncertain objective. Second, such an operator can be flexibly used and combined with many existing multi-objective optimization frameworks and techniques by just substituting their standard comparison operator, thus easily enabling the Pareto front optimization of problems with multiple uncertain objectives. Third, a new benchmark for evaluating uncertainty-aware optimization techniques is introduced by incorporating different types of uncertainties into a well-known benchmark for multi-objective optimization problems. Fourth, the new comparison operator and benchmark suite are integrated into an existing multi-objective optimization framework that features a selection of multi-objective optimization problems and algorithms. Fifth, the efficiency in terms of performance and execution time of the proposed comparison operator is evaluated on the introduced uncertainty benchmark. Finally, statistical tests are applied giving evidence of the superiority of the new comparison operator in terms of \epsilon -dominance and attainment surfaces in comparison to previously proposed approaches.

Analysis of International Mobile Roaming Services with Smart Call Assistant System in GSM Originating Call

In this research, it takes a trace log data with real testing using the Polystar and TrafficNews to know the comparison operator Telkomsel network calls with and without the SCA, as well as performance data call in roaming of Roamware SCA tools to know the Key Performance Indicator (KPI) from the parameters of the Call Setup Success Rate (CSSR) and Call Drop Rate (CDR) then be processed and analyzed to find out the quality of service the influence of SCA implementation calls the overall international operators in the three countries with the highest incoming data so that it could become the next parameter in the repair services provided. Results of the study to the difference between the signals operators are implemented with the SCA system of the inbound roaming customers. CSSR percentage in average in 3 countries, Australia, China, Singapore prior to SCA system in May of 81.48%, while after system restored by SCA of 90.98%, where after the repaired system SCA standard KPIS PT. Telkomsel i.e. normal state – good, whereas the percentage KPI failure calls (CDR) in 3 countries, Australia, China, Singapore prior to SCA system in May of 18.52%, while after the repaired system SCA amounted to 9.02%, where after improved system SCA standard KPI applied PT. Telkomsel into normal state.

The strong and the weak: evaluation in modal desideratives

<p>Modal auxiliaries can generate two desiderative readings: strong (1) and weak (2) desiderativity. These differ notably in whether they express strict preference and whether they are felicitous out of the blue.</p><p>(1) (A: Cookie anyone?) B: I would like/enjoy a cookie.</p><p>(2) #(A: Cookie anyone?) B: I would/might have/take/eat a cookie.</p><p>We provide an analysis that accounts for the contrast by introducing 1) a comparison operator ≥ as part of the subjective morphology that can be pragmatically strengthened to &gt; and 2) a criterion determining how alternative situations are introduced for comparison which allows introduction by evaluatives (<em>like</em>, <em>enjoy</em>).</p>

Modified Non-Dominated Sorting Genetic Algorithm (MNSGA-II) Applied in Multi-Objective Optimization of a Coal-Fired Boiler Combustion

This paper discussed application of modified non-dominated sorting genetic algorithm-II (MNSGA-II) to multi-objective optimization of a coal-fired boiler combustion, the two objectives considered are minimization of overall heat loss and NOx emissions from coal-fired boiler. In the first step, BP neural network was proposed to establish a mathematical model predicting the NOx emissions & overall heat loss from the boiler. Then, BP model and the non-dominated sorting genetic algorithm II (NSGA-II) were combined to gain the optimal operating parameters. According to the problems such as premature convergence and uneven distribution of Pareto solutions exist in the application of NSGA-II, corresponding improvements in the crowded-comparison operator and crossover operator were performed. The optimal results show that MNSGA-II can be a good tool to solve the problem of multi-objective optimization of a coal-fired combustion, which can reduce NOx emissions and overall heat loss effectively for the coal-fired boiler. Compared with NSGA-II, the Pareto set obtained by the MNSGA-II shows a better distribution and better quality.

Comparison Operator Edge Detection Based on Remote Sensing of Marine Oil Spill

In recent years, marine oil spill is frequent and seriously threats to the sustainable development of coastal areas and marine environment. Large Marine oil spill is difficult to clean up and pollution range is large, lasting for a long time, for the biological and ecological environment destruction, particularly serious. It is very important to take corresponding measures that how to quickly master the location of the oil spill when this event occurs. Satellite remote sensing has advantages of large, multi-temporal, all-weather, real-time, quick and economic and has become an important means of monitoring marine oil spill, playing an important role in the monitoring of marine oil spill treatment. This paper illustrates by Penglai 19-3 oil spill accident, using MODIS remote sensing data, the use of the Robert operator, Sobel operator, Laplacian operator and LOG operator to extract the oil spill edge, and extraction accuracy of the comparison and analysis.

Initial problems for neutral functional differential equations with unbounded delay

General theorems on the existence, uniqueness and convergence of successive approximations for classical solutions of the Cauchy problem are given. Results are based on a comparison method and on the axiomatic approach to equations with unbounded delay. The nonlinear comparison operator is investigated. Examples of nonlinear comparison problems and phase spaces are given.