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GSK algorithm is based on the concept of how humans acquire and share knowledge through their lifespan. Discrete Binary version of GSK named novel binary Gaining Sharing knowledge-based optimization algorithm (DBGSK) depends on mainly two binary stages: binary junior gaining sharing stage and binary senior gaining sharing stage with knowledge factor 1. These two stages enable BGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space. Besides, one of these practical applications is to optimally schedule the flights for residual stranded citizens due to COVID-19. The problem is defined for a decision maker who wants to schedule a multiple stepped trip for a subset of candidate airports to return the maximum number of residuals of stranded citizens remaining in listed airports while comprising the minimization of the total travelled distances for a carrying airplane. A nonlinear binary mathematical programming model for the problem is introduced with a real application case study, the case study is solved using (DBGSK).

This article proposes a novel binary version of recently developed Gaining-Sharing knowledge-based optimization algorithm (GSK) to solve binary optimization problems is proposed. GSK algorithm is based on the concept of how humans acquire and share knowledge during their life span. Discrete Binary version of GSK named novel binary Gaining Sharing knowledge-based optimization algorithm (DBGSK) depends on mainly two binary stages: binary junior gaining sharing stage and binary senior gaining sharing stage with knowledge factor 1. These two stages enable DBGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space.An improved scheduling of the technical counselling process for utilization of the electricity from solar energy power stations is introduced. The scheduling aims at achieving the best utilization of the available day time for the counselling group,n this regard,a new application problem is presented, which is called a Travelling Counselling Problem (TCP).A Nonlinear Binary Model is introduced with a real application

A sensitive, simple and rapid RP-HPLC method with fluorescence detection has been developed to simultaneously quantify amlodipine besylate (AML) and olmesartan medoxomil (OLM) in their combined pharmaceutical preparation. The method development was divided into three phases. In the first phase, a Plackett-Burman design (PBD) was used to screen five independent factors. The objective of the second phase was to optimize the method performance using a single factor design to obtain the best chromatographic performance for a short run time. Optimum separation was obtained using Lichrospher RP-18 (250 mm × 4.6 mm × 5 μm) column in the isocratic mode using a mobile phase of methanol and 5mM sodium dihydrogen phosphate buffer pH 2.5 (60:40, v/v). The flow rate was maintained at 1.2 mL/min and the detection was performed with a fluorescence detector set at 417 nm (λemission) after excitation at 254 nm (λexcitation). The third phase was method validation according to ICH guidelines. The method was valid in a concentration range of 175 – 325 ng/mL for AML and 250 – 1750 ng/mL for OLM. The proposed method was successfully applied for analysis of the binary mixture of two drugs in their combined pharmaceutical formulation.

Green chemistry is an emerging field concerned with safe practices in chemical method development. The purpose of the study is to develop a sensitive, environmentally friendly spectrofluorimetric method by studying and optimizing variables affecting the native fluorescence intensity of Moxifloxacin using experimental design approach. The analysis was divided into three phases: studying and screening the critical factors using 2-level full factorial design, optimization using central composite design and validation according to International Conference on Harmonization (ICH) guidelines. The optimal experimental conditions obtained from this study were 0.05 M phosphate buffer with an adjusted buffer pH of 9.7 and a temperature of 7.4°C±0.5, providing a sensitive measurement of MOX. The validated method providing to be linear over a range of 5-40ng/mL (r= 0.9999), precise, accurate, and robust (demonstrated by the Plackett-Burman design). It can be concluded that the validated method can be safe, optimum, and environmentally friendly alternative for the analysis of MOX.

Chloroquine phosphate (CQ) the antimalarial drug and suggested to treat the pandemic disease coronavirus (COVID-19) is often adulterated with some of the non-steroidal anti-inflammatory drugs (NSAIDs) such as paracetamol, aspirin (ASP), or both. The purpose of this study is to detect such counterfeited drugs, using a reversed phase high pressure liquid chromatography (RP-HPLC) method with fluorescence detection. Analysis was divided into three phases. In the first phase, a Plackett-Burman design (PBD) was used to screen five independent factors, namely, buffer pH, buffer concentration (mM), acetonitrile content (%), flow rate (mL/min) and triethylamine (TEA) content in the buffer preparation (%). The selected dependent variables were (resolution, symmetry of peaks and run time). The objective of the second phase was to optimize the method performance using Box-Behnken design (BBD) and desirability function for multiple response optimization to obtain the best chromatographic performance with the shortest run time. Optimal chromatographic separation was achieved on a YMC-pack pro C18 ODS-A column (15 cm × 4.6 mm, 5 µm) at room temperature The optimum mobile phase consisted of acetonitrile and 5 mM sodium dihydrogen phosphate buffer containing 0.5% triethyamine (30:70, v/v) with the pH adjusted to 3.5 using an orthophosphoric acid solution. The flow rate was maintained at 1 mL/min, and the detection was performed with a fluorescence detector fixed at 380 nm (λemission) after excitation at 335 nm (λexcitation). The third phase was method validation according to ICH guidelines, providing to be specific, precise, accurate, and robust. The method is linear over a range of 0.4–8 µg/mL for chloroquine and ASP, while for paracetamol it is linear over 16–48 µg/mL. The developed RP-HPLC method was used for quantitation of the three drugs in chloroquine dosage form samples. The method shows a great tendency in the classification between the genuine chloroquine and the adulterated ones in pharmaceutical preparations and breast milk.

Impurity profiling has a rising importance nowadays due to the increased health problems associated with impurities and degradation products found in several drug substances and formulations. Three advanced, accurate and precise chemometric methods were developed as impurity profiling methods for a mixture of bisoprolol fumarate (BIS) and perindopril arginine (PER) with their degradation products which represent drug impurity or a precursor to such impurity. The methods applied were Partial Least Squares (PLS-1), Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Artificial Neural Networks (ANN). Genetic Algorithm (GA) was used as a variable selection tool to select the most significant wavelengths for the three chemometric models. For proper analysis, a 5-factor 5-level experimental design was used to establish a calibration set of 25 mixtures containing different ratios of the drugs and their degradation products (impurities). The validity of the proposed methods was assessed using an independent validation set. The designed models were able to predict the concentrations of the drugs and the degradation products/impurities in the validation set and pharmaceutical formulation. The proposed methods presented a powerful alternative to traditional and expensive chromatographic methods as impurity profiling tools.

Surface-enhanced infrared absorption spectroscopy offers an alternative to conventional IR spectroscopy and utilizes the signal enhancement exerted by the plasmon resonance of nanostructured metal thin films. Citrate-capped silver nanoparticles were prepared in a single-step method, and their morphology was identified using transmission electron microscopy, scanning electron microscopy, ultraviolet/visible spectrophotometry, and Zetasizer. The nanoparticles generated were deposited on the surface of cheap aluminum slides for different durations aiming for the selection of the best time producing a thin film, suitable to act as a lab-on-a-chip SEIRA substrate. These substrates were coupled to partial least squares regression tools for simultaneous resolving of the quinary mixture in commercial dosage forms of bisoprolol, perindopril, bisoprolol acid degradation product, bisoprolol alkali degradation product, and perindoprilat in concentration ranges of 15–75, 60–300, 15–55, 12–60, and 20–80 μg/mL with limits of detection values of 0.69, 3.43, 0.97, 1.25, and 1.09 μg/mL, respectively. Overall, we could demostrate that the localized surface plasmon resonance sensor coupled to chemometrics provides cheap, simple, selective, multiplex, rapid, and molecular specific procedures for impurity detection, which would be beneficial in many applications for quality control and quality accuracy of active pharmaceutical ingredients.

Acquiring and purchasing fuel represents a significant part of operating and managing expenses for an airline, so commercial airline companies are implementing strategies for minimizing costs of fuel for their flight routes. A nonlinear mathematical model for the airline refueling problem is presented to minimize the total cost in a flight route problem. The model is enhanced to include possible discounts in fuel prices, which are performed by adding dummy variables and some restrictive constraints, or by fitting a suitable function that relates prices to the purchased amounts. The obtained fuel plan explains exactly the amounts of fuel to be purchased from each airport in the route. A case study is introduced for a certain flight rotation in a domestic US air aviation company. The mathematical model including stepped discounted fuel prices is formulated, and the results show that introducing the discounted fuel prices dramatically change the strategy of fuel purchase amounts in the aircraft flight problem.

The purpose of this paper is to present a proposal for scheduling shuttle ambulance vehicles assigned to COVID-19 patients using one of the discrete optimization techniques, namely, the multi-objective multiple 0–1 knapsack problem. The scheduling aims at achieving the best utilization of the predetermined planning time slot; the best utilization is evaluated by maximizing the number of evacuated people who might be infected with the virus to the isolation hospital and maximizing the effectiveness of prioritizing the patients relative to their health status. The complete mathematical model for the problem is formulated including the representation of the decision variables, the problem constraints, and the multi-objective functions. The proposed multi-objective multiple knapsack model is applied to an illustrated case study in Cairo, Egypt, the case study aims at improving the scheduling of ambulance vehicles in the back and forth shuttle movements between patient’ locations and the isolation hospital. The case study is solved using a novel Discrete Binary Gaining-Sharing knowledge-based optimization algorithm (DBGSK). The detail procedure of the novel DBGSK is presented along with the complete steps for solving the case study.

The aim of this paper is to introduce an improved strategy for controlling COVID-19 and other pandemic episodes as an environmental disinfection culture for public places. The scheduling aims at achieving the best utilization of the available working day-time hours, which is calculated as the total consumed disinfection times minus the total loosed transportation times. The proposed problem in network optimization identifies a disinfection group who is likely to select a route to reach a subset of predetermined public places to be regularly disinfected with the most utilization of the available day-working hours. A Nonlinear Binary Model is introduced with a detailed real application case study involving improving the scheduling of Coronavirus disinfection process for some Educational Institutions as an example of crowded public places in Cairo, Egypt. The case study mathematical model is solved using a novel Discrete Binary Gaining-Sharing knowledge-based optimization algorithm (DBGSK). The results of this study show that the novel optimization algorithm can efficiently solve the proposed Problem.

Many application problems are formulated as nonlinear binary programming models which are hard to be solved using exact algorithms especially in large dimensions. One of these practical applications is to optimally distribute protective materials for the newly emerged COVID-19. It is defined for a decision-maker who wants to choose a subset of candidate hospitals comprising the maximization of the distributed quantities of protective materials to a set of chosen hospitals within a specific time shift. A nonlinear binary mathematical programming model for the problem is introduced with a real application case study; the case study is solved using a novel discrete binary gaining-sharing knowledge-based optimization algorithm (DBGSK). The solution algorithm proposes a novel binary adaptation of a recently developed gaining-sharing knowledge-based optimization algorithm (GSK) to solve binary optimization problems. GSK algorithm is based on the concept of how humans acquire and share knowledge through their life span. Discrete binary version of GSK named novel binary gaining-sharing knowledge-based optimization algorithm (DBGSK) depends mainly on two binary stages: binary junior gaining-sharing stage and binary senior gaining-sharing stage with knowledge factor 1. These two stages enable DBGSK for exploring and exploitation of the search space efficiently and effectively to solve problems in binary space.

An improved scheduling the disinfection process of the new coronavirus (COVID-19) is introduced. The scheduling aims at achieving the best utilization of the available day time, which is calculated as the total disinfection time minus the total loss travelling time. In this regard, a new application problem is presented, which is called a travelling disinfection-man problem (TDP). The new problem (TDP) in network optimization resemble somehow the famous travelling salesman problems (TSP) but with basic distinct variations where a disinfection group is likely to select a route to reach a subset of predetermined places to be disinfected with the most utilization of the available day working hours. A nonlinear binary model is introduced with a detailed real application case study involving the improving the scheduling of coronavirus disinfection process for five contaminated faculties in Ain Shams University in Cairo, and the case study is solved using a novel discrete binary gaining-sharing knowledge-based optimization algorithm (DBGSK).

Chemometric and separation-based techniques (HPLC) are the most applicable and versatile analytical techniques for the analysis of multicomponent mixtures, in the present contribution, a comparison was highlighted between the two analytical techniques of utmost importance as stability indicating assays: UV-spectrophotometry and HPLC-UV focusing on the greenness of each for the simultaneous determination of amprolium HCl (AMP) and ethopabate (ETHOP) in the presence of their alkaline degradation products. The first method was chemometric methods applied were PLS-1, GA-PLS and GA-ANN. To compare the prediction ability of the models, a 4-factor 5-level experimental design was used to establish a calibration set of 25 mixtures containing different ratios of the drugs and their degradation products. The validity of the proposed methods was assessed using an independent validation set of 5 mixtures. The comparison between the different models showed the superiority of ANN model in solving the highly overlapped spectra of the quaternary mixture, yet using inexpensive and easy to handle instruments like the UV-VIS spectrophotometer. The ANN method was used for the quantitative analysis of the drugs in pharmaceutical dosage form via handling the UV spectral data. The second method was based on liquid chromatographic HPLC determination of AMP and ETHOP using C18 column (250 × 4.6 mm2)—PRONTOSIL 5 μm, a mobile phase consisting of methanol: Hexane sulphonic acid sodium salt at (pH = 3.4 ± 0.2) adjusted by orthophosphoric acid (55: 45 v/v). Quantitation was achieved with UV detection at 270 nm at temperature 24 °C. Linearity, accuracy and precision were found to be acceptable over the concentration range of 10.0–70.0 and 1.0–25.0 μg·mL−1 for AMP and ETHOP, respectively. The proposed methods could be successfully applied for the routine analysis of the studied drugs either in their pure bulk powders or in their pharmaceutical preparations without any preliminary separation step. The results obtained were statistically compared with those obtained by applying the reported method.

Supramolecular chemistry has gained an increasing attention in different disciplines of pharmaceutical community. Methacholine chloride (MCh) is a parasympathomimetic bronchoconstrictor which is a gold standard diagnostic tool for asthma through methacholine challenge test. The determination of MCh is a substantial analytical problem due to the lack of chromophore in its structure, therefore direct spectrophotometry becomes not possible for MCh quantification. In this work, we have exploited the high spectral absorptivity of 4-sulfocalix[4]arene (SCX4) and its exceptional complexation towards choline-mimetic guests to develop a method to quantify MCh. The host guest interaction between MCh and SCX4 produces an inclusion complex that can be investigated using different UV-spectrophotometric methods [dual wavelength method (DWM), ratio difference method (RDM) and ratio derivative method (1DD)]. The proposed methods are based on measurement of the manipulated absorbance of the formed complex peak after resolving the overlap from the host SCX4 spectrum followed by quantitation of MCh. Validation of the methods was performed in compliance with ICH guidelines, regression analysis showed good linearity over the concentration ranges of 10.0–150.0 μM for DWM and 10.0–170.0 μM for RDM and 1DD. The limit of quantification and detection were estimated to be 7.5 μM, 2.5 μM for DWM, 5.2 μM, 1.6 μM for RDM and 5.0 μM, 1.7 μM for 1DD, respectively. The complexation binding ratio and stability constant were calculated to be 1:1 and 7.20 × 104 ± 1.60 M−1, respectively, using continuous variation Job's method. Also, these methods have been used to determine MCh in Povocholine® formulation and in spiked human plasma. Moreover, the greenness of the proposed analytical procedures was evaluated by National Environmental Methods Index and Analytical Eco-Scale and the promising junction between the supramolecular chemistry and the eco-friendly spectrophotometric approaches was highlighted.

This paper proposes a nonlinear Goal Programming Model (GPM) for solving the problem of admission capacity planning in academic universities. Many factors of university admission capacity planning have been taken into consideration among which are number of admitted students in the past years, total population in the country, number of graduates from secondary schools, desired ratios of specific specialties, faculty-to-students ratio, and the past number of graduates. The proposed model is general and has been tested at King Abdulaziz University (KAU) in the Kingdom of Saudi Arabia, where the work aims to achieve the key objectives of a five-year development plan in addition to a 25-year future plan (AAFAQ) for universities education in the Kingdom. Based on the results of this test, the proposed GPM with a modified differential evolution algorithm has approved an ability to solve general admission capacity planning problem in terms of high quality, rapid convergence speed, efficiency, and robustness.

Faculty of Engineering at King Abdulaziz University plans to redesign its undergraduate courses, which is required for students in 14 different programs. These courses have an annual enrolment of about 2,500 students each year. The Operations Research Teaching Area in the Department of Industrial Engineering will be presented as a case study. This area involves two core and three elective courses. The course redesign involves preparing students for the Fundamentals of Engineering (FE) Exam requirements while coping with the best worldwide practices as benchmark. The FE Exam is a computer-based test (CBT). It is closed book with an electronic reference. Examinees have 6 hours to complete the exam, which contains multiple-choice questions. The 6-hour time also includes a tutorial and an optional scheduled break. The exam session is administered in the following seven disciplines: Chemical, Civil, Electrical and Computer, Environmental, Industrial and Systems, Mechanical, and Other Disciplines. The top ten USA Universities in Industrial/Manufacturing Engineering are used as a benchmark to reliably lead to the desired courses redesign results. Moreover, faculty experience is also utilized to enhance the process.

Linseed oil fatty acids were epoxidized by peracetic acid, then reacted with diethanolamine to give epoxidized hydroxy ethyl linseed oil fatty acid amide (I). This amide was rejected with toluene diisocyanate to produce epoxidized polyurethane-amide (II). Component I was also reacted with phthalic anhydride to give epoxidized polyesteramide (III). Resins II and III were evaluated as coating materials. The results obtained were compared with commercial epoxy resin, and show that resins II and III may be suitable to use as petroleum pipeline coatings.

Faculty of Engineering at King Abdulaziz University plans to redesign its undergraduate courses, which is required for students in 14 different programs. These courses have an annual enrolment of about 2,500 students each year. The Operations Research Teaching Area in the Department of Industrial Engineering will be presented as a case study. This area involves two core and three elective courses. The course redesign involves preparing students for the Fundamentals of Engineering (FE) Exam requirements while coping with the best worldwide practices as benchmark. The FE Exam is a computer-based test (CBT). It is closed book with an electronic reference. Examinees have 6 hours to complete the exam, which contains multiple-choice questions. The 6-hour time also includes a tutorial and an optional scheduled break. The exam session is administered in the following seven disciplines: Chemical, Civil, Electrical and Computer, Environmental, Industrial and Systems, Mechanical, and Other Disciplines. The top ten USA Universities in Industrial/Manufacturing Engineering are used as a benchmark to reliably lead to the desired courses redesign results. Moreover, faculty experience is also utilized to enhance the process. Keywords: Industrial Engineering; Course design; Best practices; Benchmark; Fundamental Engineering.

Port can be viewed as a complex system containing several entities with interfering attributes. The whole image is very complex and special care should be considered to model such systems.Several works for investigating, analysing evaluating and improving port activities are carried out, each of them is concerned with a specific area related to the port functions, the key tool for most of these works is the simulation.The purpose of this paper is to give an overview of a computer simulation program used as a management decision support tool helping in evaluating and improving the comprehensive port activities. The proposed simulation model consists from a statistical module, an input module, ship generator, cargo generator, ship operation planner, cargo handling equipment planner, warehouse controller, and the transportation means planner. All the planning and controlling modules related to ships, cargoes, warehousing and transportation means contain special optimizers the optimizers constitute operations research packages to be used whenever possible to optimize the specific process related to port operations.The computer model will have several output results; evaluating different port performance indicators, performing port improvement analysis, studying port expansion possibilities, estimating future view of the port and making an economic impact evaluation.

Intensive competition and rapid technology development of Twisted-Pair Cables (TPC) industry have left no room for competing manufacturers to harbour system inefficiencies. TPC are used in various communication and networks hardware applications; their manufacturing facilities face many challenges including various product configurations with different equipment settings, different product flows and Work in Process (WIP) space limitations. The quest for internal efficiency and external effectiveness forces companies to align their internal settings and resources with external requirements/orders, or in different words, significant factors must be set appropriately and identified prior to manufacturing processes. Integrated definition models (IDEF0, IDEF3) in conjunction with a simulation model and a design of experiments (DOE) have been developed to characterize the TPC production system, identify the significant process parameters and examine various production setting scenarios aiming to get the best product flow time.