Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, to find the optimal solution. This method also included multiple adaptive and random variables to guarantee that the solution space was explored and used in various optimization tasks. When all criteria are considered, the results of this study show that the SSA is efficient for least-distance path allocation. The simulation findings reveal a significant improvement over the well-known particle swarm optimization (PSO) algorithm, with recycling and disposal costs decreasing by 10% to 30%.
Based economic units to technology to add innovations that lead to contribute to customer satisfaction, under intense competition and rapid development in customer taste, the economic units tend to apply the concepts that contribute to customer satisfaction led by the introduction of artificial intelligence techniques. In the production prominent role in the contributing and responding to the rapid changes in customer tastes, and consequent impact this in achieving customer satisfaction. Search gained importance of relying on artificial intelligence techniques to achieve customer satisfaction through speed of response to changes in the tastes of customers and thus be able to increase its market share، and sales growth، and to achieve a
... Show MoreThere are many problems facing the economic entities as a result of its mass production &variation of its products , the matter which had increased the need & importance of cost accounting which is regarded a main tool for the managerial control.
The actual costing system is unable to meet the contemporary management needs ,so the Standard costing system appear to provide the management with required information to perform its functions by the best use& way.
This research aims to determine the standard cost for the direct material for oil extraction activity by applying it in the north oil company.
Iraqi industrial units face strong competition due to many problems including1- high production costs2- weak interest in studying the market3- lack of government support for their products4- dumping the market with imported products with specifications and a competitive price as well as adopting the traditional cost system in calculating costs that do not provide appropriate information for pricing decisions Which requires studying and analyzing these problems and dealing with them by adopting modern technologies so that they can compete, so the research aims to show the knowledge bases of technology Activity- Based Costing, with an indication of the role of technology Activity- Based Costing in rationalizing the tax In, and the
... Show MorePesticides serve a crucial function in contemporary farming practices, safeguarding agricultural crops against pest infestations and boosting production outputs. However, indiscriminate use has caused environmental and human health damage. This study aimed to develop and validate a gas chromatography-flame ionization detection (GC-FID) methodology for the direct and routine analysis of spiromesifen residues in soil, leaves, and tomato fruits. The proposed method prioritizes simplicity by avoiding derivatization steps, offering advantages over existing approaches that utilize lengthy multi-step extraction or derivatization prior to GC analysis. A key novelty of this work is the development of a QuEChERS extraction coupled directly to GC-FID
... Show MoreThe key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.
The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty
Abstract
The current research is attempt to test the reflection of the lean management on the human resources management practices of two of the most important communication companies operating in Iraq (`Zain & Asia cell), The research aims to Determine the extent of adoption of the lean management approach in the two researched companies, as it improving human resource management practices. The research problem represented in the existence of lack of in some aspects of the application the lean management approach in service sector and neglecting the impact of its tools on the human resource management practices. For this purpose three principle research hypotheses has been formulated, first there is a correlation rel
... Show MoreThis study was conducted in the poultry field of the Department of Animal Production/ College of Agricultural Engineering Sciences / University of Baghdad for the period from 42 days. Aiming to know the effect of using shrimp waste powder (Metapenaeus Affinis) and enzyme in broilers diet on physiological and microbial performance and indicators of fat oxidation in meat. 250 one-day-old ROSS308 chicks were used. The chicks were fed on diets containing shrimp waste treated with enzyme and not treated with protease enzyme by 0,4,6 %. The experiment included five treatments, with 5 replicates for each treatment, and each replicate contained 10 birds. The results showed a significant decrease (P≤0.05) in the concentration of ALT and AS
... Show MoreBP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.
In this paper, a compact genetic algorithm (CGA) is enhanced by integrating its selection strategy with a steepest descent algorithm (SDA) as a local search method to give I-CGA-SDA. This system is an attempt to avoid the large CPU time and computational complexity of the standard genetic algorithm. Here, CGA dramatically reduces the number of bits required to store the population and has a faster convergence. Consequently, this integrated system is used to optimize the maximum likelihood function lnL(φ1, θ1) of the mixed model. Simulation results based on MSE were compared with those obtained from the SDA and showed that the hybrid genetic algorithm (HGA) and I-CGA-SDA can give a good estimator of (φ1, θ1) for the ARMA(1,1) model. Anot
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