Session Program


  • 10 July 2017
  • 04:30PM - 06:30PM
  • Room: Aragonese
  • Chairs: Andrew Starkey and Gilbert Owusu

Fuzzy Logic in Service Operations

Abstract - In real world optimization problems there are often multiple objectives to consider. However, with traditional multiobjective optimization algorithms, like the Non-Dominated Sorting Genetic Algorithm, NSGA-II, one solution is not produced at the end of the process but a set of non-dominated solutions. This set of solutions make up what is known as the Pareto front. The Pareto front relies on calculating the dominance of each solution the multi-objective algorithm produces. Traditional dominance calculations are reasonable for a small number of objectives. However, the more objectives there are in the problem, the more unsuitable these dominance calculations become. This leads to poor selection criteria and ultimately a weaker form of optimization when compared to a small number of objectives. In this paper, we present a fuzzy logic system for computing dominance between two solutions. We have evaluated this fuzzy logic system in optimizing a set of black box test problems. In addition, we have also applied it to a real world many-objective system that optimizes five conflicting objectives, in the telecommunications domain. The implementation of the fuzzy logic system has led to the NSGA-II algorithm with Fuzzy Dominance Rules (FDRs) being able to perform better in a number of black box tests and improving the results of our real-world many-objective optimization problem, with a statistically significant improvement to the hypervolume of 5.46\%.
Abstract - The Message Passing Interface (MPI), which appeared in 1994, introduced many powerful functionalities for parallel processing positioning the MPI among the top preferred packages for parallel processing for researchers and developers. However, MPI-1 did not provide mechanisms for creating runtime processes. Although MPI-2 included spawn process creation, it did not specify how those dynamically created processes may be assigned to hardware processors. This resulted in poor resource allocation, load balancing, and consequently bad performance too. In this paper, the researchers discuss this problem proposing a fuzzy scheduling algorithm for dynamic processes, which proved to vastly outperform the native MPI scheduler.
Abstract - In this paper, a comparison of the behaviour of fuzzy decision trees and gradual fuzzy decision trees is presented in a real-world application in the context of labour economics. The aim of this study is on one hand to present, in a real case, the good property of interpretability of such decision trees. On the other hand, it shows the importance to take into account a graduality relation between attributes and the class during the construction of a fuzzy decision tree. The obtained results illustrate the differences between the two types of fuzzy decision trees.
Abstract - In this work we propose an approach of multicriteria decision making (MCDM) using Elimination Et Choice Transiting Reality (ELECTRE) methods, interval-valued intuitionistic fuzzy (IVIF) sets and possibility theory. The proposition concerns the computation of concordance sets and discordance sets using possibility measures. The proposed approach is applied to select the best investment projects decision problem from literature. Therefore results are compared and concluding remarks are given.
Abstract - The article is a review of the perspective methods and approaches to the design of fuzzy decision support systems (DSS) with the application of discrete fuzzy inference engine. The authors also developed a two-stage method for fuzzy rule base (RB) correction in the case of changing the structure of the input vector. In addition, the fuzzy DSS with a hierarchical structure for the best selection of the marine delivery company was developed. Simulation results confirm the effectiveness and feasibility of fuzzy DSS structure with variable input coordinates vector, in particular, in marine practice.
Abstract - The concept of stratification (CST) is a reform in problem solving approaches in computer science introduced and developed by Lotfi Zadeh [1]. In this innovative approach, the target set is the initial states. The environment around the target is then systematically identified and stratums around the target are gradually built using the concept of 'incremental target enlargement'. We advocate that this approach is useful in different areas; however, it is essential to highlight the potential applicability of the approach by presenting different examples. In this paper illustrative examples in Information Dominance (ID) and in requirement elicitation in contracting, are structured using CST. These examples illustrate the application of the concept in the contexts of logistic informatics and contracting and assists the modelling process. Of particular relevance are Example 4 and 5. Example 4 exposes situations that are not dealt with in the current form of CST. The study, therefore, extends CST by considering the possibility of occasional state repetition while using the same input. Further, a 3D version of CST is structured and proposed for future applications. This proposed version of the concept illustrates how the Fuzzy Inference System (FIS) benefits the user when applying CST.