The classical PERT approach uses the path with the largest expected duration as the critical path to estimate the probability of completing a network by a given deadline. However, in general, such a path is not the most critical path (MCP) and does not have the smallest estimate for the probability of completion time. The main idea of this paper is derived from the domination structure between ...

Proper scheduling of tasks leads to optimum using of time and resources, in order to obtaining best result. One of the most important and complicated scheduling problems is open shop scheduling problem. There are n jobs in open shop scheduling problem which should be processed by m machines. Purpose of scheduling open shop problem is attaining to a suitable order of processing jobs by specified...

This paper is a continuation of Part I [9]. First, the extension of fuzzy theories is studied and the important deduction theorem is proved which is a generalisation of the corresponding classical one. In Section 7.3, algebraic properties of the set of formulae are studied. This section serves as a preparation for the proofs of the most important theorems in this paper which are the completenes...

Over the years, significant developments have taken place in the direction of clustering numeric, categorical or mixed data. A new challenge is to cluster data with missing attribute values. The early algorithms used Fuzzy c-means to partition data into fuzzy clusters and estimate the missing values through estimation algorithms. Recently, Hathaway and Bezdek have proposed four strategies for e...

Among other applications, multi-adjoint lattices have been successfully used for modeling flexible notions of truth-degrees in the fuzzy extension of logic programming called MALP (Multi-Adjoint Logic Programming). In this paper we focus in the completion of such mathematical construct by adapting the classical notion of Dedekind-MacNeille in order to relax this usual hypothesis on such kind of...

Missing value is a challenging issue in data mining, as information deficiency negatively affects both data quality and reliability. This paper focuses on an algorithm of a fuzzy clustering approach for missing value imputation with noisy data immunity. The PCFKMI (Pre-Clustering based Fuzzy K-Means Imputation) method aggregates data instances to more accurate clusters for further appropriate e...