A note on the use of a fuzzy approach in adaptive partitioning algorithms for global optimization

Demirhan, Melek; Özdamar, Linet

doi:10.1109/91.784211

Cited by 14 publications

(14 citation statements)

References 24 publications

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“…The FT proposed here is related to the fuzzy adaptive partitioning algorithm (FAPA) developed for global optimization [8], [9] and it differs from FAPA in two major aspects. These are 1) FT has to work with a limited number of data collected prior to its implementation, whereas FAPA goes on taking samples under the guidance of the partitioning/assessment process; and 2) FT uses an overlapping partitioning scheme rather than the nonoverlapping approach found in FAPA, and it analyzes the data multiple times with a systematically changing overlap rate to achieve the following three goals: a) To utilize the information extracted from the set of given data more efficiently, because data found in intersection areas of partitions contribute to more than one data sets simultaneously; b) to form and assess different data clusters resulting from applying varying overlap rates between neighboring partitions so that different classification topologies might be obtained for the site and unified; and c) to increase classification reliability by imposing multiple control before including a given block in the set of noncontaminated blocks.…”

Section: Ft Approachmentioning

confidence: 99%

Fuzzy Tessellation Approach for Environmental Site Characterization

Özdamar

Demirhan

2005

IEEE Trans. Syst., Man, Cybern. C

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Environmental site investigations are carried out prior to the reclamation of industrially contaminated sites. It is required to take samples and analyze the laboratory reports to find out the distribution of contaminants over the site. In this study, an algorithm based on fuzzy assessment and overlapped partitioning is proposed to identify the topology of polluted areas in a given industrial site. The primary objective is to locate contaminated zones accurately with sparse data in a preliminary investigation and the second is to reduce the size of the area that is resubjected to expensive sampling methods (such as deep drilling) in the detailed phase of the investigation. If these objectives are achieved, a considerable cost reduction occurs in the process of site characterization.

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Section: Ft Approachmentioning

confidence: 99%

Fuzzy Tessellation Approach for Environmental Site Characterization

Özdamar

Demirhan

2005

IEEE Trans. Syst., Man, Cybern. C

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“…For the fuzzy approach, the degree of membership of any point, is measured by the membership function µ i,k of the function to minimize For the evaluation of µ i,k , several formulations are possible [7], we can mention the S -membership function, the Gaussian membership function or the linear membership function.…”

Section: Potential Of a Sub Region And Decision Factormentioning

confidence: 99%

“…The potential of a space can be evaluated using interval, statistical estimation techniques or fuzzy approach [7].…”

Section: Potential Of a Sub Region And Decision Factormentioning

confidence: 99%

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A two phase local global search algorithm using new global search strategy

Boudjehem

Mansouri²

2006

Journal of Information and Optimization Sciences

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In this paper, we present a two phase local global search algorithm that is used to remedy the problems associated to the presence of sensitive local optima. However, The presence of such optima in most optimization problems make the global optimization very difficult in the sense that, as soon as the design space exhibits such local optima, the optimization method falls inside and are unable to leave it to a potentially better region. To accurate this problem we propose a new global search technique, which is called Circular Design. We propose also a new point scattering design and a new population evolution scheme the new algorithm works on the principal of evaluating a set of super individuals only. The local search is invoked at each time where a reallocation of the center of the Circular Design is needed, and it has the ability of significantly enlarge the attraction basin of the global optimum in order to reduce the probability of a possible convergence to an interesting local optimum. To illustrate the effectiveness of the proposed algorithm, numerical applications are performed with different benchmark problems; and the obtained results are satisfactory in terms of the solution quality and the time need to reach the global optimum.

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“…Hence in both cases (7) is satisfied. The proof for the general case, where the partitioning iterations do not necessarily take place in nested sub-regions, is given in [27].…”

Section: Composite Uncertaintymentioning

confidence: 99%

A Fuzzy Adaptive Partitioning Algorithm (FAPA) for Global Optimization

Demirhan

Özdamar

2003

Fuzzy Sets Based Heuristics for Optimization

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Abstract. Adaptive Partitioning Algorithms (APA) divide the feasible region into non-overlapping partitions (regions) in order to direct the search to the promising region(s) that are expected to contain the global optimum. APA usually collect data from pre-determined locations in each partition and use evaluation measures that are based on assumptions or function approximations. The proposed Fuzzy Adaptive Partitioning Algorithm (FAPA) is a novel approach that aims at locating the global optimum of multi-modal functions without using any assumptions or approximations. FAPA introduces two new features: it selects the locations of data randomly in each partition and it utilizes a fuzzy measure in assessing regions.

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A note on the use of a fuzzy approach in adaptive partitioning algorithms for global optimization

Cited by 14 publications

References 24 publications

Fuzzy Tessellation Approach for Environmental Site Characterization

Fuzzy Tessellation Approach for Environmental Site Characterization

A two phase local global search algorithm using new global search strategy

A Fuzzy Adaptive Partitioning Algorithm (FAPA) for Global Optimization

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