The teaching-learning-based optimization (TLBO) algorithm is finding a large number of applications in different fields of engineering and science since its introduction in 2011. The major applications are found in electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics, chemistry, biotechnology and economics. This paper presents a review of applications of TLBO algorithm and a tutorial for solving the unconstrained and constrained optimization problems. The tutorial is expected to be useful to the beginners.

The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO) algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO) algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front) maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009) competition. The performance assessment is done by using the inverted generational distance (IGD) measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

The present problem deals with the thermo-elastic interaction of a gold nano-beam resonator induced by ramp-type heating under the two temperature theory of generalized thermoelasticity. The governing equations are constructed in the context of two-temperature three-phase-lag model (2T3P) and two-temperature Lord-Shulman (2TLS) model of generalized thermoelasticity. Using the Laplace transform, the fundamental equations have been expressed in the form of a vector-matrix differential equation which is then solved by Eigen value approach and Mathematica software package has been used as a tool. The inversion of Laplace transforms are computed numerically using the method of Fourier series expansion technique. Numerical results for lateral vibration, temperature, displacement, stress, and the strain energy are presented graphically for Lord-Shulman model and also for three-phase lag model. A numerical instance of gold nano-beam in femtoseconds scale has been calculated to present the effect of the ramping time parameter on the entire studied field. The effect of two-temperature parameter is also discussed on the physical fields.

In this paper we develop an inventory model for deteriorating items with price sensitive demand. Generally the vendor offers a cash discount or fix time period to the retailer to pay all the dues. According to the availability of money the retailer chooses his/her option. In this paper we discuss the possible cases of permissible delay and cash discount. The shortages are allowed in this model and are partially backlogged. Holding cost is considered as varying function of time, which reflects a more realistic concept. The purpose of this study is to optimize the overall cost of the system and to compute optimal ordering quantity. Numerical examples for different cases are also presented to illustrate the study. A sensitivity analysis with regard to distinct associated parameters is shown to make sure the constancy of the model.

This paper concentrates on the evaluation of reliability measures of a computer system of two-identical units having independent failure of h/w and s/w components. Initially one unit is operative and the other is kept as spare in cold standby. There is a single server visiting the system immediately whenever needed. The server conducts preventive maintenance of the unit after a maximum operation time. If server is unable to repair the h/w components in maximum repair time, then components in the unit are replaced immediately by new one. However, only replacement of the s/w components has been made at their failure. The priority is given to the preventive maintenance over repair activities of the h/w. The time to failure of the components follows negative exponential distribution whereas the distribution of preventive maintenance, repair and replacement time are taken as arbitrary. The expressions for some important reliability measures of system effectiveness have been derived using semi-Markov process and regenerative point technique. The graphical behavior of the results has also been shown for a particular case.

The machinability of a material can be defined as the ease with which it can be machined. Materials with good machinability property require less power to cut, can be cut quickly, and easily obtain a good finish without wearing the tooling much. Therefore, to manufacture components economically, production engineers are challenged to discover ways to determine machinability of materials which mainly depends on their mechanical properties, as well as on other cutting conditions. In this paper, the machinability characteristics of alloys of three materials, i.e. aluminium, copper and steel are studied applying grey TOPSIS (technique for order preference by similarity to ideal solution) method. For each case, eight different alloys are considered whose machinability is evaluated based on different mechanical properties which are expressed in grey numbers. Using the adopted methodology, it now becomes easier for the manufacturers to select a particular alloy that can be easily machined. It is observed that A357RC, CuCr1Zr and AISI 5140 are the best machinable aluminium, copper and steel alloys, respectively. It is also found that the ranking performance of grey TOPSIS method remains unaffected with the variation in greyness of the considered mechanical property values.

Piroxicam (POC) and oxfendazole (OFA) are two widely used veterinary non-steroidal anti-inflammatory and anthelmintic medicines, respectively. Simple, precise and accurate and cost-effective methods for the determination of POC and OFZ in bulk drug and in its dosage forms have been developed and validated. The methods are based on the potentiometric titration of compound with acetous perchloric acid in glacial acetic acid medium using modified glass-saturated calomel electrode system. The methods are applicable over the ranges 1.5 - 15 mg and 7.5-15 mg, for POC and OFA, respectively. The proposed methods were successfully applied to the determination of active substances in their pharmaceutical dosage forms. A statistical comparison was made on the results of proposed methods with those obtained for reference method. The intra-day and inter-day precision and accuracy values obtained were satisfactory with RSD and RE values less than 3%. Excipients in tablets did not interfere to the assay as shown by the recovery study via standard addition technique with mean percentage recoveries in the range 97.8 – 100.6%.

Electrochemical micromachining (EMM) appears to be a very promising micromachining process for having higher machining rate, better precision and control, reliability, flexibility, environmental acceptability, and capability of machining a wide range of materials. It permits machining of chemically resistant materials, like titanium, copper alloys, super alloys and stainless steel to be used in biomedical, electronic, micro-electromechanical system and nano-electromechanical system applications. Therefore, the optimal use of an EMM process for achieving enhanced machining rate and improved profile accuracy demands selection of its various machining parameters. Various optimization tools, primarily Derringer’s desirability function approach have been employed by the past researchers for deriving the best parametric settings of EMM processes, which inherently lead to sub-optimal or near optimal solutions. In this paper, an attempt is made to apply an almost new optimization tool, i.e. differential search algorithm (DSA) for parametric optimization of three EMM processes. A comparative study of optimization performance between DSA, genetic algorithm and desirability function approach proves the wide acceptability of DSA as a global optimization tool.

The outset of new technologies, systems and applications in manufacturing sector has no doubt lighten up our workload, yet the chance causes of variation in production system cannot be eliminated completely. Every produced/ordered lot may have some fraction of defectives which may vary from process to process. In addition the situation is more susceptible when the items are deteriorating in nature. However, the defective items can be secluded from the good quality lot through a careful inspection process. Thus, a screening process is obligatory in today’s technology driven industry which has the customer satisfaction as its only motto. Moreover, in order to survive in the current global markets, credit financing has been proven a very influential promotional tool to attract new customers and a good inducement policy for the retailers. Keeping this scenario in mind, the present paper investigates an inventory model for a retailer dealing with imperfect quality deteriorating items under permissible delay in payments. Shortages are allowed and fully backlogged. This model jointly optimizes the order quantity and shortages by maximizing the expected total profit. A mathematical model is developed to depict this scenario. Results have been validated with the help of numerical example. Comprehensive sensitivity analysis has also been presented.

In this paper, an inventory model is studied with ramp type demand rate where holding cost is expressed as linearly increasing function of time. The study includes some features that are likely to be associated with certain types of inventory, like inventory of seasonal fruits and vegetables, newly launched fashion items, etc. When stock on hand is zero, the inventory manager offers a price discount to customers who are willing to backorder their demand. The optimum ordering policy and the optimum discount offered for each backorder are determined by minimizing the total cost in a replenishment interval.