Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best solution. When it is the better one, it replaces with the artificial fish swarm solution from which this solution was improvised. Meanwhile the best improvised solutions are carried over to the Harmony Memory. The objective is to minimize a total completion time (makespan) and to make the proposed approach as a portion of the expert and the intelligent scheduling system for remanufacturing decision support. Harmony search algorithm has demonstrated to be efficient, simple and strong optimization algorithm. The ability of exploration in any optimization algorithm is one of the key points. The obtained optimization results show that the proposed algorithm provides better exploitation ability and enjoys fast convergence to the optimum solution. As well, comparisons with the original artificial fish swarm algorithm demonstrate improved efficiency.
The research aims to determine the principles of total quality management (commitment of senior management, product planning, customer satisfaction, process improvement) and its role in promoting employee loyalty through a sample survey of the opinions of managers in public redemption Company. Which amounted to (45) individuals adoption of the questionnaire as a tool head in collecting data and information and their responses were analyzed using several statistical methods, which included (arithmetic mean, standard deviation, correlation coefficient, and the coefficient of simple regression) depending on the program (spss). The research found a group of the most important conclusions from the presence
... Show MoreThe university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a
... Show MoreIslamic law has relied on a number of sources in order to denote the rulings issued by them, including what is original and what is sub, and it is known to all scholars, that the Prophet's Sunnah is the second major source after the Koran, which separated the overall and devoted its year and restricted absolute. God Almighty obeyed the owner and his followers, and that his obedience of obedience to God Almighty said: (Who obeys the messenger has obeyed God) (women: 80), and then between the peasant who believes in him and his victory and follow him, he said: (and he said: And the one who was revealed with them were the successful ones (al-A'raf: 157).
It is known that the Sunnah commanded to follow is the
Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce
... Show MoreThe Islamic Issue did not rise the “widespread arguments” in contemporary times, just as the issue of applying Islamic Law. Just as the Islamic forces used this purpose, or employed it during their march to reach to power by adopting the sacred as motivation towered the power, or control the governance. However, the reality show that this goal remained within the boundaries of slogans in the sense of a teleological slogan, and did not go beyond the limits of advocacy or arrangement as the primary source of legislation with differences of teleological reasoning, in a manner that reflected an intellectual problem about the validity of the use of this concept or the ability to apply and enforce the law in today's world, to impose
... Show MoreIn this paper, a least squares group finite element method for solving coupled Burgers' problem in 2-D is presented. A fully discrete formulation of least squares finite element method is analyzed, the backward-Euler scheme for the time variable is considered, the discretization with respect to space variable is applied as biquadratic quadrangular elements with nine nodes for each element. The continuity, ellipticity, stability condition and error estimate of least squares group finite element method are proved. The theoretical results show that the error estimate of this method is . The numerical results are compared with the exact solution and other available literature when the convection-dominated case to illustrate the effic
... Show MoreIn this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from
... Show MoreNowadays, information systems constitute a crucial part of organizations; by losing security, these organizations will lose plenty of competitive advantages as well. The core point of information security (InfoSecu) is risk management. There are a great deal of research works and standards in security risk management (ISRM) including NIST 800-30 and ISO/IEC 27005. However, only few works of research focus on InfoSecu risk reduction, while the standards explain general principles and guidelines. They do not provide any implementation details regarding ISRM; as such reducing the InfoSecu risks in uncertain environments is painstaking. Thus, this paper applied a genetic algorithm (GA) for InfoSecu risk reduction in uncertainty. Finally, the ef
... Show MoreImplementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.
Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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