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%.
Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCG
... Show MoreThe aim of present work is to study the removal of phenol present in aqueous feed solution by the emulsion liquid membrane technique using kerosene as a diluent, sodium hydroxide as a stripping agent, and sorbitan monooleate (Span 80) as a surfactant. The parameters studied were: surfactant concentration, volume ratio of membrane phase to internal phase, and stirring speed. It was found that more than 98% of phenol can be removed at the conditions were surfactant concentration 2% (v/v), volume ratio of membrane phase to internal phase 5:1 and stirring speed 400 rpm. Maximum phenol extraction efficiency at 7 minutes of process time was observed. It was found that there was a good agreement between the standard kerosene an
... Show MorePurpose: To contribute to the development of an appropriate program for the management of medical waste based on clear-cut principles in order to reach the overall goal of improving the public health and environment of the population in our country.
Design / Approach / Introduction: The research is based on the analytical descriptive approach as a method of study in the field of data collection using a check list and analysis of the data through the use of some statistical treatments.
Results: The need is to establish a medical waste management in hospitals and follow international standards in all stages of waste management from sorting, collection, transportation and treat
... Show MoreAbstract : A research was conducted to study the process parameters affecting hexavalent chromium Cr (VI) (carcinogenic compound) the removal percentage from the electrical industries company waste water that contain 88 mg/l of Cr (VI) concentration by adsorption onto tea wastes. Synthetic water with 88 mg/l Cr (VI) concentration was used. Several operation parameters affecting Cr (VI) removal efficiency were investigated, such as pH, initial Cr (VI) concentration, stirring time and tea wastes dose. The experimental results reveal that maximum Cr (VI) removal reached up to 94.26% at pH of 2, stirring time of 180 minute, tea wastes do
... Show MoreReactive Powder Concrete (RPC) is one of the most advanced recent high compressive strength concrete. This work explored the effects of using glass waste as a fractional replacement for fine aggregate in reactive powder concrete at levels of 0%, 25%, 50%, and 100%. Linear and mass attenuation coefficients have been calculated as a function of the sample's thickness and bremsstrahlung energy. These coefficients were obtained using energy selective scintillation response to bremsstrahlung having an energy ranging from (0.1-1.1) MeV. In addition, the half-value thickness of the samples prepared has been investigated. It was found that there is a reversal association between the attenuation coefficient and the energy of the bremsstrahlu
... Show MoreThe present study is to investigate the possibility of using wastes in the form of scrap iron (ZVI) and/ or aluminum ZVAI for the detention and immobilization of the chromium ions in simulated wastewater. Different batch equilibrium parameters such as contact time (0-250) min, sorbent dose (2-8 g ZVI/100 mL and 0.2-1 g ZVAI/100 mL), initial pH (3-6), initial pollutant concentration of 50 mg/L, and speed of agitation (0-250) rpm were investigated. Maximum contaminant removal efficiency corresponding to (96 %) at 250 min contact time, 1g ZVAI/ 6g ZVI sorbent mass ratio, pH 5.5, pollutant concentration of 50 mg/L initially, and 250 rpm agitation speed were obtained.
The best isotherm model for the batch single Cr(III) uptake by ZVI
... Show More<p>In combinatorial testing development, the fabrication of covering arrays is the key challenge by the multiple aspects that influence it. A wide range of combinatorial problems can be solved using metaheuristic and greedy techniques. Combining the greedy technique utilizing a metaheuristic search technique like hill climbing (HC), can produce feasible results for combinatorial tests. Methods based on metaheuristics are used to deal with tuples that may be left after redundancy using greedy strategies; then the result utilization is assured to be near-optimal using a metaheuristic algorithm. As a result, the use of both greedy and HC algorithms in a single test generation system is a good candidate if constructed correctly. T
... Show MoreIn this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.
Today’s academics have a major hurdle in solving combinatorial problems in the actual world. It is nevertheless possible to use optimization techniques to find, design, and solve a genuine optimal solution to a particular problem, despite the limitations of the applied approach. A surge in interest in population-based optimization methodologies has spawned a plethora of new and improved approaches to a wide range of engineering problems. Optimizing test suites is a combinatorial testing challenge that has been demonstrated to be an extremely difficult combinatorial optimization limitation of the research. The authors have proposed an almost infallible method for selecting combinatorial test cases. It uses a hybrid whale–gray wol
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