Fuzzy sets and systems
P. K. Halder; C. L. Karmarker; B. Kundu; T. Daniel
Abstract
Recently, the competitiveness and awareness of productivity have increased rapidly among different industries. Hence, the performance evaluation of the criteria affecting the productivity is needed to improve productivity and strengthen the management of the organization. In Bangladesh, Ready Made Garments ...
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Recently, the competitiveness and awareness of productivity have increased rapidly among different industries. Hence, the performance evaluation of the criteria affecting the productivity is needed to improve productivity and strengthen the management of the organization. In Bangladesh, Ready Made Garments (RMGs) is one of the most probable and profitable sectors which is considered as the main economic strength of the country. In this study, a two-phased research method has been projected to find out some governing factors affecting industry’s output. In the first phase, six criteria associated with the productivity have been identified based on literature, inputs from experts, opinions from the officials and managers of six garments industries in Bangladesh. In the second phase, among different MCDM tools, Fuzzy Analytic Hierarchy Process (FAHP) has been used for evaluating criteria weights and ranking the criteria. Among several criteria, line-balancing criterion has been found as the most important factor to improve the RMG’s productivity.
Engineering Optimization
K. Chitra; P. Halder
Abstract
In today’s competitive environment completing a project within time and budget, is very challenging task for the project managers. This aim of this study is to develop a model that finds a proper trade-off between time and cost to expedite the execution process. Critical path method (CPM) is used ...
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In today’s competitive environment completing a project within time and budget, is very challenging task for the project managers. This aim of this study is to develop a model that finds a proper trade-off between time and cost to expedite the execution process. Critical path method (CPM) is used to determine the longest duration and cost required for completing the project and then the time-cost trade–off problem (TCTP) is formulated as a linear programming model. Here, LINDO program is used to determine the solution of the model. To implement the proposed model, necessary data were collected through interviews and direct discussion with the project managers of Chowdhury Construction Company, Dhaka, Bangladesh. The analysis reveals that through proper scheduling of all activities, the project can be completed within 120 days from estimated duration of 140 days. Reduction of project duration by 17% is achieved by increasing cost by 3.73%, which is satisfactory.
Engineering Optimization
C. L. Karmaker
Abstract
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 ...
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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.