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Solution for Multi-Objective Optimisation Master Production Scheduling Problems Based on Swarm Intelligence Algorithms
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The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), Teaching Learning Based Algorithm and Harmony Search Algorithm (GA, TLBO and HS). This segment of the research constitutes of two parts the first emphasises on the outcome of the five simulation algorithms and then identifies the best, while the second part is about comparing the best with the search algorithm work in 2009, the applicability of BAT Algorithm and Gravitational Search Algorithm (GSABAT) to planning problems, the technique used for calculating master production scheduling, and the very important results and recommendations for future studies

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Publication Date
Wed Mar 01 2023
Journal Name
Al-khwarizmi Engineering Journal
A Methodology for Evaluating and Scheduling Preventive Maintenance for a Thermo-Electric Unit Using Artificial Intelligence
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Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Solution of Regular Singular Initial Value Problems
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    This paper devoted to the analysis of regular singular initial value problems for ordinary differential equations with a singularity of the first kind , we propose semi - analytic technique using two point osculatory interpolation to construct polynomial solution, and discussion behavior of the solution in the neighborhood of the regular singular points and its numerical approximation, two examples are presented to demonstrate the applicability and efficiency of the methods. Finally , we discuss behavior of the solution in the neighborhood of the singularity point which appears to perform satisfactorily for singular problems.

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
A Direct Solution Scheme for Wide-Angle Electromagnetic Scattering Problems Using Compressive Sensing-Based Method of Moments
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Publication Date
Sat Sep 27 2014
Journal Name
Soft Computing
Multi-objective evolutionary routing protocol for efficient coverage in mobile sensor networks
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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Multi-Objective Set Cover Problem for Reliable and Efficient Wireless Sensor Networks
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Achieving energy-efficient Wireless Sensor Network (WSN) that monitors all targets at
all times is an essential challenge facing many large-scale surveillance applications.Singleobjective
set cover problem (SCP) is a well-known NP-hard optimization problem used to
set a minimum set of active sensors that efficiently cover all the targeted area. Realizing
that designing energy-efficient WSN and providing reliable coverage are in conflict with
each other, a multi-objective optimization tool is a strong choice for providing a set of
approximate Pareto optimal solutions (i.e., Pareto Front) that come up with tradeoff
between these two objectives. Thus, in the context of WSNs design problem, our main
contribution is to

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Publication Date
Sun Mar 28 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
WOAIP: Wireless Optimization Algorithm for Indoor Placement Based on Binary Particle Swarm Optimization (BPSO)
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Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received s

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Generating dynamic S-BOX based on Particle Swarm Optimization and Chaos Theory for AES
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Data security is a significant requirement in our time. As a result of the rapid development of unsecured computer networks, the personal data should be protected from unauthorized persons and as a result of exposure AES algorithm is subjected to theoretical attacks such as linear attacks, differential attacks, and practical attacks such as brute force attack these types of attacks are mainly directed at the S-BOX and since the S-BOX table in the algorithm is static and no dynamic so this is a major weakness for the S-BOX table, the algorithm should be improved to be impervious to future dialects that attempt to analyse and break the algorithm  in order to remove these weakness points, Will be generated dynamic substitution box (S-B

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Publication Date
Thu Jan 01 2015
Journal Name
Progress In Electromagnetics Research C
BANDWIDTH OPTIMISATION FOR SEMICONDUCTOR JUNCTION CIRCULATORS
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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
Wireless Optimization Algorithm for Multi-floor AP deployment using binary particle swarm optimization (BPSO)
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Abstract<p>Optimizing the Access Point (AP) deployment is of great importance in wireless applications owing the requirement to provide efficient and cost-effective communication. Highly targeted by many researchers and academic industries, Quality of Service (QOS) is an important primary parameter and objective in mind along with AP placement and overall publishing cost. This study proposes and investigates a multi-level optimization algorithm based on Binary Particle Swarm Optimization (BPSO). It aims to an optimal multi-floor AP placement with effective coverage that makes it more capable of supporting QOS and cost effectiveness. Five pairs (coverage, AP placement) of weights, signal threshol</p> ... Show More
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