International Journal of Research in Industrial Engineering
Volume:6 Issue: 3, Autumn 2017

Exponential smoothing is a sophisticated forecasting method that works based on previous forecast plus a percentage of the forecast error. A key issue of this technique is the proper choice of exponential smoothing constant. In order to minimize forecasting errors, choosing an appropriate value of smoothing constant is very crucial. In this study, a framework is developed for the selection of optimal value of smoothing constant that minimizes a measure of forecast errors like mean square error (MSE) and mean absolute deviation (MAD). Both “trial & error” and Excel based non-linear optimizer (“Excel Solver”) are used for this purpose. To validate the proposed model, necessary demand data of Ruchi Jhal Muri from years 2010-2016 from Square Food & Beverage Ltd. in Mohakhali, Dhaka were collected. The optimum values of smoothing constant under trial & error method are 0.31 and 0.14 for minimum MAD and MSE respectively whereas for excel solver, values are 0.314 and 0.143 with respect to minimum MAD and MSE. Although both methods provide approximately the same results but excel solver is much easier & requires less time for deriving optimum solution. This study will provide an outline for the forecast planners as well as manufacturers to improve the accuracy of exponential forecasting through using Excel Solver for determining the optimum value of smoothing constant.

In the last years, several techniques have been reported for managing a system and recognition of the related decision making units. One of them is based on mathematical modeling. Efficiency of any system is very important for all decision makings. Often applied data have time dependent inputs/ outputs. To calculate the efficiency of time dependent data, a new calculation method has been developed and reported here. By this method, the efficiency has been calculated, with minimum errors and minimum mathematical solving model. The data are often time dependent, therefore Spline function has been estimated as a function of time, without using any particular time. Based on this developed function, the efficiency of time dependent data of a numerical example has been calculated and reported.

In this paper, a solution procedure is proposed to solve Fully Fuzzy Linear Fractional Programming (FFLFP) problem where all the variables and parameters are triangular fuzzy numbers. Here, FFLFP problem transformed into an equivalent Multi- Objective Linear Fractional Programming (MOLFP) problem. Then MOLFP converted into an equivalent multi objective linear programming problem by using mathematical programming approach. The proposed solution illustrated through numerical examples and compared with existing methods.

Supplier selection is one of the most critical activities of purchasing management in a supply chain. Because selecting right suppliers helps reduce purchasing costs, improve quality of final products and services, etc. In a real situation, for a supplier selection problem, most of the input information is not known precisely, since decision making deal with human judgment and comprehension and its nature includes ambiguity. In fact, on the one hand, deterministic models cannot easily take this vagueness into account. In these cases, the theory of fuzzy sets is one of the best tools to handle uncertainty. On the other hand, Kumar et al. proposed a new approach to find the fuzzy optimal solution of fully fuzzy linear programming problem. So, using this approach in this paper, we present a new mixed integer multi objective linear programming model for supplier selection problem. Due to uncertainty of the data, in continuation, we present a new method to solve multi objective fully fuzzy mixed integer linear programming and implement the method to supplier selection problem. Computational results present the application of the method and the proposal solving method.

This study examines some concessioned airports in the developed countries and their operational performance level with a view to identifying the positive impact of concessioning on their growth, development and operational performance. The ultimate goal of the study is to provide basis for adapting the experience from lessons learnt to Nigeria’s airports as a strategy for realization of airport operational efficiency. The study advocated for the concessioning of two principal airports in Nigeria because of their potentials to enhancing the application of the experience learnt from lessons on concessioning in the developed countries. Data obtained from relevant Government Institutions and Agencies in Nigeria were analyzed using descriptive statistics. It was concluded that Lagos and Abuja International Airport are the two major airports in Nigeria that can be privatized or concessioned in order to improving their level of efficiency. Happenings around the world have shown the efficacy of Government disengagement in running business through the policy of concessioning and privatization. Airport concessioning and privatization has been considered as a major tool to enhance airport efficiency as witnessed in the developed countries. Airport concessioning has the capacity to enhance efficiency of airport operation; reduce cost of airport services to stakeholders; decrease cost to the government for the support of airport sector; and attract private sector participation to free public resources for public services.

Incompressible Jeffrey fluid under peristalsis is considered into permeable conduit. Magnetic effect and slip effect are studied for this channel in the existence of wall slip and heat transfer. Time average velocity, heat transfer coefficient and temperature are obtained analytically underneath the presumption of large wavelength approximation and also small Reynolds number. Effects of magnetic number, slip parameter, elasticity parameters and Brinkman number on coefficient of heat transfer and temperature field are graphically discussed.  It is observed that in the case of temperature distribution the flow intensity enhances with rise in the Darcy number, while it reduces with enhancement in the Brinkman number and slip parameter.

The present study aims to removal of copper ions (Cu2+) as a heavy metal ion from aqueous solution by a high inorganic molecular weight compound. This compound is modified clay (activated bentonite) which is used in oil well drilling, and obtained from local company. The experimental results showed that it is an adsorption reaction that follows Langmuir isotherm model. The maximum removal of copper ions was obtained at low copper ion initial concentration, high adsorbent dosage, low temperature, and high agitation speed. It is clear from the results obtained that the compound within the experimental range investigated cannot be considered as a method for the removal of waste stream within the experimental range investigated as the residual concentration is higher than the limits which are allowed by the environmental limits which are allowed by the low which is 5 ppm. These results may be due to the high initial copper concentration used in this work and low dosage of the compound.