Industrial Mathematics
Ramin Barati; Sara Fanati Rashidi
Abstract
This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee ...
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This study aims to verify the main factors influencing turnover intention in the Iran hospitality industry. The objective of this study is to construct a fuzzy AHP and fuzzy TOPSIS model to evaluate the dimensions of the hotel employee turnover intention model. The performance evaluation for employee turnover intention includes Work Itself, Supervision, Coworkers Relationship, Salary and Benefit, Career Opportunities, Job Stress, Perceived Risk, and Job Insecurity. These dimensions generate a final evaluation for ranking priority among the employee turnover intention of the proposed model. The importance of dimensions is evaluated by 20 experts, and decision-making is processed through the fuzzy concept and fuzzy environment. From the critical fuzzy AHP and fuzzy TOPSIS analysis results, the study shows that the most important dimensions of employee turnover intention in the hotel industry model are salary and benefits. Moreover, the results indicate that the least important dimensions are the Co-workers Relationship, Supervision, and Career Opportunities. The second group dimensions that impact employee turnover in the context of the COVID-19 epidemic are Work Itself, Job Stress Perceived Risk, and Job Insecurity. In addition, this study’s results show that three-star hotels have the highest value of turnover intention; the second is the Four and Five-star hotels, and the third is the Below three-star hotels. The results of the study will help businesses in the field of hospitality have a more comprehensive view of human resource management activities. Especially, this study provides implications for hotel managers in understanding employee behavior and their turnover intention during the context of the COVID-19 epidemic based on the eight proposed dimensions.
Industrial Mathematics
Mohammad Shafiekhani; Alireza Rashidi Komijan; Hassan Javanshir
Abstract
In this paper, a new type of vehicle routing problem in the valuable commodity transportation industry is modeled considering the route risk constraint. The proposed model has two objective functions for risk minimization. In the first objective function, three concepts are presented, which are: 1) the ...
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In this paper, a new type of vehicle routing problem in the valuable commodity transportation industry is modeled considering the route risk constraint. The proposed model has two objective functions for risk minimization. In the first objective function, three concepts are presented, which are: 1) the vehicle does not travel long distances in the first three moves because it carries more money, 2) to serve the same branch on two consecutive days, at the same time 3) The bow should not be repeated in two consecutive days. This reduces the possibility of determining a fixed pattern for the service and increases the security of the service. In the second objective function, risk is a function of the amount of money, the probability of theft and the probability of its success. To solve the proposed model, two different meta-heuristic algorithms including genetic algorithm and ant colony optimization algorithm have been used. In computational testing, the best parameter settings are determined for each component and the resulting configurations are compared in the best possible settings. The validity of the answers of the algorithms has been investigated by generating different problems in various dimensions and using the real information of Shahr Bank. The results show that the genetic algorithm provides better results compared to the ant colony algorithm with an average of 0.93% and a maximum of 1.87% difference with the optimal solution.
Industrial Mathematics
Laith O Mazahreh; Ibrahim M. Abu-Alshaikh
Abstract
In this paper, layerwise finite element analysis for the free vibration behavior of two-dimensional functionally graded sandwich plates with different boundary conditions is presented. The plates consist of three layers; a functionally graded layer embedded between ceramic and metal isotropic layers. ...
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In this paper, layerwise finite element analysis for the free vibration behavior of two-dimensional functionally graded sandwich plates with different boundary conditions is presented. The plates consist of three layers; a functionally graded layer embedded between ceramic and metal isotropic layers. The layerwise approach is based on the third order shear deformation theory for the middle layer, while the first order shear deformation theory is used to model both the upper and lower isotropic layers. Quadrilateral 8-noded element with 13-degrees of freedom per node is used for this purpose. The present results show very good agreements with the published analytical results of plates consist of a single functionally graded layer. Furthermore, for sandwich plates good agreements were obtained when the present results are compared with similar problems solved by other methods in literature. Parametric studies were investigated for various plate parameters including applied boundary conditions, volume fraction exponents and plate side to thickness ratio.
Industrial Mathematics
Sunadi Sunadi; Humiras Hardi Purba; Dana Santoso Saroso
Abstract
The purposes of this study are, first, analyzing why the Capability Process (Cpk) index of Drop Impact Resistance (DIR) does not meet the customer requirement or below 1.33, second, finding out what improvements should be made to make it meet the specifications. Statistical Process Control (SPC) is a ...
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The purposes of this study are, first, analyzing why the Capability Process (Cpk) index of Drop Impact Resistance (DIR) does not meet the customer requirement or below 1.33, second, finding out what improvements should be made to make it meet the specifications. Statistical Process Control (SPC) is a method used in this research with supporting other tools such as Cause and Effect Diagrams (CED), Nominal Group Techniques (NGT) and why, what, where, when, and how (5W1H) method. After improvement was made, the results of the study were satisfactory, the average of DIR test was increased by 26.21% i.e. from 20.41 cm to 25.76 cm, standard deviations reduced from 1.80 to 1.48, and the potential Cpk increased significantly from 0.48 to 1.79. The SPC supported by other statistical tools was effective and efficient to improve quality, so the process statistically can be categorized as in control. At the end of this research, the further discussion is still needed to maintain what has been achieved and also to make the research even better. It is recommended for further researchers to examine the chemical composition of aluminum M1 alloy 3104 influence on the strength of the drop impact resistance and to analyze data. It is recommended to integrate or combine SPC with Six Sigma or Engineering Process Control (EPC).
Industrial Mathematics
Mohamad Ali Movafaghpour
Abstract
The Analytic Hierarchy Process (AHP) which was developed by Saaty is a decision analysis tool. It has been applied to many different decision fields. Acquiring Pairwise Comparison Matrices (PCM) is the main step in AHP and also is frequently used in other multi-criteria decision-making methods. In a ...
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The Analytic Hierarchy Process (AHP) which was developed by Saaty is a decision analysis tool. It has been applied to many different decision fields. Acquiring Pairwise Comparison Matrices (PCM) is the main step in AHP and also is frequently used in other multi-criteria decision-making methods. In a real problem when the number of alternatives/criteria to be compared is increased, the number of Pairwise Comparisons (PC) often becomes overwhelming. Since the Decision Maker’s (DM) performance in representing the relative preferences tends to deteriorate in such cases, it is preferred to gather fewer data from each individual DM in the form of pairwise comparisons. Missing values in Pairwise Comparison Matrices (PCM) in AHP is a spreading problem in areas dealing with great or dynamic data. The aim of this paper is to present an efficient mathematical programming model for estimating preference vector of pairwise comparison matrices with missing entries.
