New series of fused 1,2,4-triazoles, i.e., 3-(4-isopropylphenyl)-6-substituted phenyl-[1,2,4]triazolo[3,4-b][1,3,4]thiadiazoles (5a-5j) have been synthesized via a four-step procedure and using eco-friendly reaction condition at some steps of the synthesis. It was adopted by the formation of hydrazide of methyl 4-isopropylbenzoate (1) followed by reaction with CS2 in basic media to afford potassium salt, which on cyclized to our essential step, 4-amino-5-(4-isopropylphenyl)-4H-1,2,4-triazole-3-thiol (4). The desired adducts (5a-5j) were formed by (4) on reaction with various aromatic acids in POCl3 media. The newly synthesized triazolo- thiadiazoles have been characterized by different spectroscopic techniques and investigated for their in vitro antibacterial and antifungal activity. It was revealed that the compounds 5a, 5c, 5h, and 5i showed interesting antibacterial and antifungal activity compared to the used reference standard.

Public security is an area of increasing importance in Brazil, as society requires that public resources are managed more efficiently and effectively. Criminalistics is an integral and vital part of the Brazilian public security system and requires new management tools to optimize human resources, equipment, and facilities allocation. Faced with a challenging scenario of budgetary constraints in several areas in public administration, the search for innovative methods should be a priority for the forensic service sector managers. The current article presents a multicriteria decision model to evaluate the operational viability of 23 forensic units within the Federal Police of Brazil (PF). The framework used the hybrid approach BWM and R-TOPSIS. The proposed model led to the complete ranking of 23 local forensic units. Amongst the last positions in the ranking, it was possible to recommend merging or shutting down some units. The sensitivity analysis performed did not show abrupt variations in the original positions, confirming the robustness of the proposed solution. It was concluded that the model allowed resources optimization whilst not compromising the quality of the services provided to society.

In the present paper, four π-conjugated materials, based on terphenyl and pyrrole, with A–D–A structure have been theoretically studied to propose new organic compounds to be used in the organic solar cell field. Moreover, the geometrical and optoelectronic properties of the designed molecules M1, M2, M3 and M4 have been computed after optimization in their fundamental states, using the quantum chemical method DFT / B3LYP/ 6−311G (d, p). Different parameters including HOMO and LUMO energy levels, bandgap energy, frontier molecular orbital (FMO), chemical reactivity indices, the density of states (DOS), Voc, electrostatic potential (ESP), and thermodynamic parameters at several temperatures in the range of 0-500 K have been determined. The absorption properties including the transition energy, the wavelengths (λmax), the excitation vertical energy, and the corresponding oscillator strengths of these molecules have been studied using the quantum chemical method TD−DFT / CAM–B3LYP / 6–311G (d, p). The obtained results of our studied compounds show that M3 (with 2H, 2'H-1, 1'-biisoindole moiety) as a donor group has special optoelectronic, absorption, and good photovoltaic characteristics. Thus, they can be utilized as an electron-donating in organic solar cells BHJ type.

During the past two decades, there has been an increase on maritime freight traffic particularly in container flow. Thus, the Berth Allocation Problem (BAP) can be considered among the primary optimization problems encountered in port terminals. In this paper, we address the Dynamic Berth Allocation Problem (DBAP) in a conventional layout terminal which differs from the popular discrete layout terminal in that each berth can serve multiple vessels simultaneously if their total length is equal or less than the berth length. Then, a Modified Sailfish Optimizer (MSFO) meta-heuristic based on hunting sailfish behavior is developed as an alternative for solving this problem. Finally, computational experiments and comparisons are presented to show the efficiency of our method against other methods presented in the literature in one hand. We also discuss the productivity of a container terminal based on different scenarios which can happen.

This paper proposes a new hybrid algorithm to solve the multi-compartment vehicle routing problem (MCVRP) with a heterogeneous fleet of vehicles for the fuel delivery problem of a previous study of twenty petrol stations in northeastern Thailand. The proposed heuristic is called the Fisher and Jaikumar Algorithm with Adaptive Large Neighborhood Search (FJA-ALNS algorithm). The objective of this case is to minimize the total distance, while using a minimum number of multi-compartment vehicles. In the first phase, we used the FJA to solve the MCVRP for the fuel delivery problem. The results from solving the FJA were utilized to be the initial solutions in the second phase. In the second phase, a hybrid algorithm, namely the FJA-ALNS algorithm, has been developed to improve the initial solutions of the individual FJA. The results from the FJA-ALNS algorithm are compared with the exact method (LINGO software), individual FJA and individual ALNS. For small-sized problems (N=5), the results of the proposed FJA-ALNS and all methods provided no different results from the global optimal solution, but the proposed FJA-ALNS algorithm required less computational time. For larger-sized problems, LINGO software could not find the optimal solution within the limited period of computational time, while the FJA-ALNS algorithm provided better results with much less computational time. In solving the four numerical examples using the FJA-ALNS algorithm, the result shows that the proposed FJA-ALNS algorithm is effective for solving the MCVRP in this case. Undoubtedly, future work can apply the proposed FJA-ALNS algorithm to other practical cases and other variants of the VRP in real-world situations.

The pharmaceutical combination of Teneligliptin Hydrobromide hydrate (TEN) and Metformin Hydrochloride (MET) drugs is used in the treatment of type 2 diabetes mellitus. A new analytical method: QuEChERS (Quick, Easy, Cheap, Effective, Rugged, Safe) has been developed for the quantification of Teneligliptin (TEN) and Metformin (MET) in bulk and tablet dosage forms. The analysis was performed on Agilent symmetry analytical column Eclipse plus C18 (150 mm × 4.6 mm, 5 μm) ultra- performance liquid chromatography-Diode Array Detectors (UHPLC-DAD), while the detection was performed on 233 nm using Diode Array Detectors. Buffer and acetonitrile (65:35 v/v) were the mobile phase, run at a flow rate of 0.7 mL min−1 for isocratic elution. The buffer used in the mobile phase contained 50 mM potassium di-hydrogen phosphate, pH adjusted to 3.5±0.02 with orthophosphoric acid. The mean values of recovery were found to be 100.50% and 99.81%. The proposed method could be ideal for quantitative evaluation in pharmaceutical preparations of these drugs and also for their quality control in bulk manufacturing. Stress test covers: acid, base, peroxide, thermal and photolytic degradation; were conducted to show the specificity of the method and degradation.

Transnational corporations, which operate in competitive global marketplaces, have to build the best possible intra-supply chain model for meeting, on time, clients’ need for multiple products with the requisite quality. Since fabrication capacity is always limited, the introduction of the external provider option can assist in leveling utilization, smoothing manufacturing schedules, eliminating overtime usage, and shortening the length of the fabrication cycle. Seeking to support intra-supply chain planning, this research aims to provide a concurrent decision on rotation cycle length and delivery frequency for a multi-item vendor-buyer incorporated type of intra-supply chain system with an external provider and rework. First, a model is built to represent this hybrid inventory replenishing problem. Then, renewal reward theory, mathematical derivation, and Hessian matrix equations are utilized to arrive at the expected total cost of the model, as well as the best policies for both cycle time and distribution. Last, the applicability and sensitivity analyses of our results are exhibited by a numerical demonstration. The insights obtained from this study about critical system-related information, such as the individual and joint impacts of the variation in outsourcing and reworking-related features on the system’s optimal operating policy and various performance parameters, will offer crucial help to the managerial functions of planning and decision making in firms using this realistic multi-item hybrid intra-supply chain system.

It is a fact accepted by everybody that football is the most popular sport around the world. The result of a derby match may be very important for millions of people. Even the time seems to stop on a match day for so many people. Show and entertainment are the most important aspects of football. If soccer players have a high performance, a match may provide pleasure and excitement to audiences. Briefly, the performance and quality of soccer players are the key factors, which draw audiences. Goalkeepers are also one of the important components of football like other players playing different positions such as strikers, mid-fielders, and defenders. Moreover, a goalkeeper can affect the result of a match positively or negatively. Therefore, with the help of a mathematical approach as the methodological framework, it can be seen that the examination of the performance of goalkeepers can be beneficial for decision-makers performing in the fields of sport and the future studies. The current paper proposes an improved integrated multi-criteria decision-making approach to evaluate the selection of goalkeepers; and this model can be applied for goalkeeper’s performance analysis. The proposed model combines the weights of criteria calculated with the help of both the CRITIC and the PSI techniques by applying the weight aggregation operator. It also ranks the decision alternatives by implementing the WASPAS technique based on the final criteria weights obtained by using the weight aggregation operator. In addition, a comprehensive sensitivity analysis consisting of three stages was performed to verify the validation of the suggested hybrid model. It has been observed that A11 has remained the best option for all scenarios. As a result, the results of the sensitivity analysis prove that the proposed hybrid MCDM technique is a very useful, strong and applicable approach. Also, the results obtained by applying the proposed model are accurate, realistic, and reasonable according to the results of the validation test.

The processing time of the machine is assumed fixed in several studies. In many real industrial applications, the processing time is affected by learning and forgetting effects. This research proposes a scheduling approach to support a manufacturing system under learning/forgetting effect. The approach is supported by a Multi-Agent System to perform the scheduling activities in a quasi-real-time and in general manufacturing systems. A simulation environment is developed to test the proposed approach and the results are compared with a benchmark model for evaluating several performance measures of the manufacturing system. The simulation results highlight how the proposed approach improves all the performance measures under different conditions of inter-arrival time, learning and forgetting rates. A complete Analysis of the Variance highlights the main effects on the performance measures to support the decision maker of the manufacturing system.

The multiple travelling salesman problem (MTSP) is one of the widely studied combinatorial optimization problems with various theoretical and practical applications. However, most of the studies intended to deal with classical MTSP, very limited attention has been given to an open multiple travelling salesman problem and its variants. In this paper, an open multiple travelling salesman problem with load balancing constraint (OMTSPLB) is addressed. The OMTSPLB differs from the conventional MTSP, in which all the salesmen start from the central depot and need not come back to it after visiting the given number of cities by accomplishing the load balance constraint, which helps in fairly distributing the task among all salesmen. The problem aims to minimize the overall traversal distance/cost for operating open tours subject to the load balancing constraint. A zero-one integer linear programming (0-1 ILP) model and an efficient metaheuristic genetic algorithm (GA), is established for the OMTSPLB. Since no existing study on OMTSPLB, the proposed GA is tested on the relaxed version of the present model, comparative results are reported. The comparative results show that the proposed GA is competent over the existing algorithms. Furthermore, extensive experiments are carried out on OMTSPLB and the results show that proposed GA can find the global solution effectively.