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Showing 2 results for Sabri-Laghaie
Solving Flexible Job Shop Scheduling with Multi Objective Approach
Arash Motaghedi-Larijani, Kamyar Sabri-Laghaie , Mahdi Heydari,
Volume 21, Issue 4 (IJIEPR 2010)
Abstract

  In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Pareto-optimal solutions in a reasonable run time. The algorithm utilizes from a local search heuristic for improving the chance of obtaining more number of global Pareto-optimal solutions. The solution method uses from a perturbed global criterion function for guiding the search direction of the hybrid algorithm. Computational experiences show that the hybrid algorithm has superior performance in contrast to previous studies .


The SCAN Method to Monitor Cryptocurrency Transactions
Fatemeh Elhambakhsh, Kamyar Sabri-Laghaie,
Volume 33, Issue 1 (IJIEPR 2022)
Abstract
The fourth industrial revolution has changed our lives by enabling everyone to be interconnected virtually. A trustworthy system is required to secure large volume of stored data in IoT-based devices. Blockchain technology has led to transfer and to save data in a safe way. With this in mind, the blockchain-based cryptocurrencies have gained quite a bit of popularity because of their potential for financial transactions. In this regard, monitoring transactions network is very fruitful to find users’ abnormal behaviors. In this research, a novel procedure is used to monitor blockchain cryptocurrency transactions network. To do so, a random, binary graph model is used to simulate the transactions between users, and a SCAN method is used to detect the abnormal behaviors in the simulated model. Also, a multivariate exponentially weighted moving average (MEWMA) control chart is used to monitor centrality measures. The probability of signal is used to assess the performance of the SCAN method and that of the MEWMA control chart in distinguishing abnormalities. Then, the procedure is adopted to a Bitcoin transactions dataset.
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