A Critical Review of “A Practical Guide to Select ality Indicators for Assessing Pareto-Based Search Algorithms in Search-Based So ware Engineering”: Essay on ality Indicator Selection for SBSE
نویسندگان
چکیده
This paper presents a critical review of the work published at ICSE’2016 on a practical guide of quality indicator selection for assessing multiobjective solution sets in search-based software engineering (SBSE). This review has two goals. First, we aim at explaining why we disagree with the work at ICSE’2016 and why the reasons behind this disagreement are important to the SBSE community. Second, we aim at providing a more clari ed guide of quality indicator selection, serving as a new direction on this particular topic for the SBSE community. In particular, we argue that it does matter which quality indicator to select, whatever in the same quality category or across di erent categories. This claim is based upon the fundamental goal of multiobjective optimisation — supplying the decision-maker a set of solutions which are the most consistent with their preferences.
منابع مشابه
A Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network
Abstract Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...
متن کاملImproving of Feature Selection in Speech Emotion Recognition Based-on Hybrid Evolutionary Algorithms
One of the important issues in speech emotion recognizing is selecting of appropriate feature sets in order to improve the detection rate and classification accuracy. In last studies researchers tried to select the appropriate features for classification by using the selecting and reducing the space of features methods, such as the Fisher and PCA. In this research, a hybrid evolutionary algorit...
متن کاملTask Scheduling Using Particle Swarm Optimization Algorithm with a Selection Guide and a Measure of Uniformity for Computational Grids
In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...
متن کاملTask Scheduling Using Particle Swarm Optimization Algorithm with a Selection Guide and a Measure of Uniformity for Computational Grids
In this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the Selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. Scheduling algorithms play an important role in grid computing, parallel tasks Scheduling and sending them to ...
متن کاملAN EFFICIENT OPTIMIZATION PROCEDURE BASED ON CUCKOO SEARCH ALGORITHM FOR PRACTICAL DESIGN OF STEEL STRUCTURES
Different kinds of meta-heuristic algorithms have been recently utilized to overcome the complex nature of optimum design of structures. In this paper, an integrated optimization procedure with the objective of minimizing the self-weight of real size structures is simply performed interfacing SAP2000 and MATLAB® softwares in the form of parallel computing. The meta-heuristic algorithm chosen he...
متن کامل