This paper considers a practical truncated traveling salesman problem (TTSP), in which the salesman is only required to cover a subset of out of given cities (rather than covering all the given cities as in conventional travelling salesman problem (TSP)) with minimal traversal distance. Thus, every feasible solution tour contains exactly cities including the starting city. However, extensive research on TSP has been received and various efficient solution techniques including exact, heuristic, and metaheuristic algorithms are devoted, a very limited attention has been given to TTSP models because of its solution structure. The TTSP model comprises two types of problems including city selection i.e. as a salesman's trip need not include all the cities, the challenge is to identify which combination of cities are to be visited and which sequence of cities will constitute minimal traversal distance. A hybrid genetic algorithm (GA) comprising sophisticated mutation operators is developed to tackle this problem efficiently. Comparative computational findings suggest that the proposed GA has capability to outperform existing approaches in terms of TTSP results. In addition, the proposed GA report improved results and will serve as a basis for forthcoming TTSP studies.

Layout design and selection often have notable effects on the performance of the manufacturing industry. This research investigates the Multi-Criteria Decision Making (MCDM) approach to find out the optimum plant layout design. The proposed methodology is demonstrated through the real-life setting for the gearbox manufacturing industry. Manual and computerized layout generation approach is used efficiently and accordingly, six layout designs are generated. The approach takes into account qualitative as well as quantitative performance criteria for the selection of layout design. Analytical Hierarchy Process (AHP) is applied to obtain the weight of qualitative measures. Ranking of alternatives is obtained through the application of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum-Product Assessment (WASPAS) both integrated with the Entropy method. Empirical findings indicate that the rank acquired using the TOPSIS method is perfectly parallel to those acquired through the WASPAS method, which confirms the applicability and potential of these methods. Also, the effect of the parameter λ in WASPAS method on performance score is stable. At the same time, this paper analyses the rank reversal phenomenon and proves that the ranking proposed by TOPSIS satisfies ranking stability.

Rank reversal in decision making is a common phenomenon resulting in confusion and ambiguity in selection procedure especially while multiple multi-criteria decision making (MCDM) techniques are independently applied. To eradicate this confusion, this paper proposes a novel MCDM methodology namely Technique of Accurate Ranking Order (TARO). The TARO method is an extension of conventional MCDM approaches. The proposed method commences at the end of conventional methodologies with the final selection values. The proposed technique, using an advanced version of entropy weighting method, initially measures weights of the final selection values. Subsequently, based on the final section values and their computed weights, TARO measures accurate selection indices that determine the accurate ranking order of the alternatives. The proposed technique is illustrated by three real life examples on robot selection problems. The results obtained by TARO justify the validity, applicability and requirements of the proposed techniques for proper decision making under the MCDM environment.

A series of isoxazole derivatives, 3-aryl-5-[5-(4-nitrophenyl)-2-furyl]-2,3-dihydroisoxazoles (5a-j) were synthesized by cyclocondensation reaction between 1-aryl-3-[5-(4-nitrophenyl)-2-furyl]prop-2-en-1-ones (4a-j) and hydroxylamine hydrochloride in presence of sodium acetate in glacial acetic acid at reflux temperature. Formerly, compounds (4a-j) were synthesized by the condensation of 5-(4-nitrophenyl) furan-2-carbaldehyde (3) with various aromatic ketones by using alkali as catalyst. The structures of the synthesized various isoxazole have been characterized by using elemental analysis, Infrared,¹H-NMR spectroscopy and further supported by Mass spectroscopy. All the products have been screened for their in-vitro biological assay like antibacterial activity towards Gram-positive and Gram-negative bacterial strains and antifungal activity towards Aspergillus niger at a concentration of 40 µg/ml. It was exposed that the compounds 5a, 5c, 5e, 5f, and 5i showed inspiring antibacterial and antifungal activity compared to the used reference standard.

Additive manufacturing has been one of the most used techniques in the recent years because of its capabilities to fabricate complex structures as required by customer and industrial need from a 3D computer-aided design model without the usage of any tooling, dies and heavy machinery makes it a step ahead in the present manufacturing techniques. In the current study the author’s focus on the welding or joining of additive manufactured Polylactic acid (PLA) parts made by Fused Deposition Modeling (FDM). There are several techniques for welding these additive manufactured parts. This study mainly focuses on the joining of 3D printed PLA parts using a 3D pen and investigations on its mechanical properties experimentally. It is a very cheap and effective technique when compared to the other welding methods. This could overcome the drawback of small bed size in most 3D printers by joining smaller parts and it can also be used for repairing the defects caused during the 3D printing. Moreover the experimental testing of the mechanical properties also confirmed that the tensile, flexural and impact strength of 3D pen welded specimens retrieved above 70% of the strength to the original PLA specimen proving it to be a very effective method.

Glass Fiber Reinforced Polymer (GFRP) is a polymer composite material used in lightweight structures. This study provides insight into achieving robust GFRP H-section short-column spliced connections using bonded, bolted, and hybrid connections. The design specifications for steel splicing connections are based on BS EN 1990 and BS EN 1991 guidelines. Based on the samples subjected to axial loading, factors such as compressive strength, bonding and bearing resistance, compression behavior of the connection, and failure modes of the structure are investigated. The study includes the behavioral characteristics and results of 25 GFRP H-section Spliced connections, with each H-section measuring 152 x 72 x 6.4 mm and standing 350 mm in height. This study also examines the behavior of a composite splice joint made up of steel cover plates and steel bolts that are used to create an ideal non-bearing spliced connection. This model is used to compare to the other models to understand the behavior of spliced joints designed with GFRP cover plates. This paper holds design specifications of connections that have displayed compressive strengths of 82.35 %, 89.82 %, and 92.83 % compared to that of an un-cut GFRP H-section subjected to axial loading.

The development of three simple, precise, efficient, and accurate spectrophotometric techniques that manipulate ratio spectra is undertaken to measure Ivabradine and Carvedilol simultaneously in bulk and tablet formulation. Applying mathematical calculations like the ratio derivative, first-order ratio derivative and ratio derivative subtraction method has been used for determination of CVD and IBD. For Carvedilol, the calibration curve is linear between concentrations of 40–65 µg/mL and 50–81.25 µg/mL for Ivabradine. These strategies have been put into practice and used for analyzing marketed pharmaceutical formulations. Further, the outliers were statistically assessed by using Grubb’s test and found, as null hypothesis cannot be rejected. The suggested approach was evaluated using four green evaluation approaches with which these tools found an excellent green outcome. Altogether, the proposed method was found to be a simple, sensitive, accurate and eco-friendly method for the analysis of drugs that have overlapping properties in the UV spectrum.

With increasing concerns and challenges to climate change in recent years, green operations management (GOM) has gained significant attention from society for achieving sustainable growth. GOM is a set of practices that can be applied in production processes to produce goods with improved productivity and significantly reduced threats of carbon emission to the environment and Mother Nature. GOM mainly includes green manufacturing, green design, green logistics, and green purchases. In the paper, fuzzy best-worst method (FBWM) is used to determine the best and worst criteria affected by GOM practices. Thus, the paper attempts to explicitly analyze and highlight the significance of GOM in preserving the environment and manage the triple bottom line for achieving overall sustainable business operations.

In the world of digitization, e-commerce practices has become more popular and attracts manufacturers to combine their traditional retail channel with an e-channel. To add some salient features in the existing study, this study develops an optimal pricing and profit decision model for manufacturer-led dual-channel supply chain configurations; namely Vertically Integrated Dual-Supply Chain (VID-SC), Decentralized Dual-channel Supply Chain (DD-SC), Partially Integrate Dual-Supply Chain (PID-SC) and Horizontally Integrated Dual-Supply Chain (HID-SC). The aim of this study is to examine the effect of selected decision parameters namely cooperative advertisement, delivery lead time and free-riding on price and profit of manufacturer-led dual supply chain configurations. A linear programming for profit maximization is developed and backward induction method is used to find the optimum values of price and profit. A numerical analysis is performed to evaluate the effect of selected decision parameters on price and profit. To check the robustness of the outcomes an interaction plot is made to indicate the relationship between the selected decision parameters on optimum price. The best fit values of these decision parameters lead to the optimum price and the profit. The study helps to find the best fit value of the selected decision parameters for their specified dual-channel configuration. As a result, the model contributes as a guideline moreover it is proficient to guide manufacturers and channel members as a decision making practices without actual implementation of any strategy or policy.

Jaya algorithm has recently been proposed, which is simple and efficient meta-heuristic optimization technique and has received a great attention in the world of optimization. It has been successfully applied to some thermal, design and manufacturing associated optimization problems. This paper aims to analyze the performance of Jaya algorithm for permutation flow-shop scheduling problem which is a well-known NP-hard optimization problem. The objective is to minimize the makespan. First, to make Jaya algorithm adaptive to the problem, a random priority is allocated to each job in a permutation sequence. Second, a job priority vector is converted into job permutation vector by means of Largest Order Value (LOV) rule. An exhaustive comparative study along with statistical analysis is performed by comparing the results with public benchmarks and other competitive heuristics. The key feature of Jaya algorithm of simultaneous movement towards the best solution and going away from the worst solution enables it to avoid being trapped in the local optima. Furthermore, the uniqueness of Jaya algorithm compared with any other evolutionary based optimization technique is that it is totally independent of specific parameters. This substantially reduces the computation effort and numerical complexity. Computational results reveal that Jaya algorithm is efficient in most cases and has considerable potential for permutation flow-shop scheduling problems.