Operations Research
Hajar Shirneshan; Ahmad Sadegheih; Hasan Hosseini-Nasab; Mohammd Mehdi Lotfi
Abstract
Due to the importance of the health field, the problem of determining the shift scheduling of care providers has been addressed in many studies, and various methods have been proposed to solve it. Considering different skills and contracts for care providers is one of the essential issues in this field. ...
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Due to the importance of the health field, the problem of determining the shift scheduling of care providers has been addressed in many studies, and various methods have been proposed to solve it. Considering different skills and contracts for care providers is one of the essential issues in this field. Given the uncertainty in patients' demands, it is a crucial issue as to how to assign care providers to different shifts. One area facing this uncertainty is the provision of services to cancer patients. This study develops a stochastic programming model to account for patient demand uncertainty by considering different skills and contracts for care providers. In the first step, care providers are assigned to work shifts, then, in the second step, the required overtime hours are determined. The sample average approximation method is presented to determine an optimal schedule by minimizing care providers' regular and overtime costs with different contracts and skills. Then, the appropriate sample size is 100, determined based on the Monte Carlo and Latin Hypercube methods. In the following, the lower and upper bounds of the optimal solution are calculated. As the numerical results of the study show, the convergence of the lower and upper bounds of the optimal solution is obtained from the Latin Hypercube method. The best solution is equal to 189247.3 dollars and is achieved with a difference of 0.143% between the upper bound and lower bounds of the optimal solution. The Monte Carlo simulation method is used to validate the care provider program in the next stage. As shown, in the worst case, the value of the objective function is equal to 197480 dollars.
Operations Research
Elham Samadpour; Rouzbeh Ghousi; Ahmad Makui; Mehdi Heydari
Abstract
In Home Health Care (HHC) operations, one of the major aims of HHC centers is to timely meet patients' demands. According to the feedback from HHC centers, their decision-makers deal with some complexity in scheduling and routing of their health workers. Inspired by this point, the present research introduces ...
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In Home Health Care (HHC) operations, one of the major aims of HHC centers is to timely meet patients' demands. According to the feedback from HHC centers, their decision-makers deal with some complexity in scheduling and routing of their health workers. Inspired by this point, the present research introduces a new HHC routing and scheduling problem considering different skill levels of health workers and different levels of patients’ needs. So, in such a condition, a highly qualified health worker can visit those patients who need lower-skilled demands while a low-qualified health worker cannot visit those who request higher skills. In this way, the total cost of the system will be lower compared to the situation in which the patients' needs exactly match the health workers' skills. Moreover, we consider that the maximum number of homes each health worker is tasked to visit during the day is specified and if more patients than this specified limit are assigned to each health worker, an additional cost will be imposed on the center in proportion to the excess number of patients. Since patient satisfaction, which is obtained with timely visits, is important for each HHC center, a hard time window is considered for each patient. The presented model is solved using the GAMS software with the CPLEX solver. Along with the MIP approach, a metaheuristic algorithm based on a Simulated Annealing (SA) algorithm is adopted to solve the problem. The results give the managers insight into this method of cost management in comparison with manual and traditional traditional planning. This study may help the decision-makers of HHC centers make more accurate decisions which, in turn, result in timelier service provision, increase the patients' satisfaction level, and improve the overall efficiency of HHC centers.
Operations Research
Vahid Razmjooei; Iraj Mahdavi; Selma Gutmen
Abstract
A Cellular Manufacturing System (CMS) is a suitable system for the economic manufacture of part families. Scheduling the manufacturing cells plays an effective role in successful implementation of the manufacturing system. Due to the fact that in the CMS, bottleneck machine and human resources are two ...
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A Cellular Manufacturing System (CMS) is a suitable system for the economic manufacture of part families. Scheduling the manufacturing cells plays an effective role in successful implementation of the manufacturing system. Due to the fact that in the CMS, bottleneck machine and human resources are two important factors, which so far have not been studied simultaneously in a mathematical model, there should be a model to consider them. Therefore, this research develops a bi-objective model for CMS in a three-dimensional space of machine-part and human resources. The main objective is to minimize the maximum completion time of all tasks in the system and reduce the number of intercellular translocation based on bottleneck machines’ motion and human resources. Due to the NP-hardness of the studied problem, applying the conventional solution methods is very time-consuming, and is impossible in large dimensions. Therefore, the use of metaheuristic methods will be useful. The accuracy of the proposed model is investigated using LINGO by solving a small example. Then, to solve the problem in larger dimensions, a hybrid Multi-Objective Tabu Search-Genetic Algorithm (MO-TS-GA) is designed and numerical results are reported for several examples.
Operations Research
Seyed Amin Badri; Negar Yarmohamadi
Abstract
The aim of this paper is to propose a mathematical model for two dental centers in a competitive market of dental tourism. Dental tourists are looking for cheaper treatment with proper quality, and dental centers are looking to maximize their profits by providing services to tourists. Government also ...
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The aim of this paper is to propose a mathematical model for two dental centers in a competitive market of dental tourism. Dental tourists are looking for cheaper treatment with proper quality, and dental centers are looking to maximize their profits by providing services to tourists. Government also monitors dental centers by setting tariffs (subsidies or taxes). This problem is modeled and solved in the form of Stackelberg (or Leader-Follower) game. The government as the leader determines the amount of tariffs and then the dental centers as the followers simultaneously determine the price and quality level of their services. To solve the game, first the equilibrium values related to the price and quality level of the services of the dental centers have been calculated by Nash equilibrium. Then, according to the equilibrium values obtained for dental centers, the optimal amount of tariffs are calculated. Finally, to clarify the proposed model a numerical example is provided and sensitivity analysis is performed on some parameters. In this paper, for the first time a mathematical model is developed for pricing and determining the quality of services in a competitive market of dental tourism. The obtained results indicate that increasing the amount of subsidy will lead to a decrease in the prices of service provided by the dental centers. Moreover, by increasing the amount of subsidies allocated to the dental centers, the government can expand the dental tourism industry.
Operations Research
Chuck Extrand; Janet Hoskin; Martin Eeg
Abstract
Many factors may influence the accuracy of part count by weight, but one of the most ubiquitous and often overlooked causes is part variability. In this work, experiments were performed to quantify the weight variation of injection molded parts and to measure the maximum number of those parts that could ...
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Many factors may influence the accuracy of part count by weight, but one of the most ubiquitous and often overlooked causes is part variability. In this work, experiments were performed to quantify the weight variation of injection molded parts and to measure the maximum number of those parts that could be accurately counted by weight. A model and working equations that account for tolerances of both the mold cavity and plastic were derived to estimate how part variability affects the weight counting of a single set of parts. Within experimental uncertainty, the model gave estimates that agreed with the actual part counts.
Operations Research
Walid Meslameni; Chokri Ben Salem
Abstract
Bending is one of the most frequently used processes in the sheet metal products industry. The major users are mainly the automotive, aeronautics and electrical engineering industries. It is necessarily a cold forming operation of a flat material, with or without lubricant, obtained notably by exceeding ...
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Bending is one of the most frequently used processes in the sheet metal products industry. The major users are mainly the automotive, aeronautics and electrical engineering industries. It is necessarily a cold forming operation of a flat material, with or without lubricant, obtained notably by exceeding its elastic limit. After retraction of the tools and relaxation of the stresses, a springback consequently occurs and a permanent deformation persists causing certain geometric modifications of the product. As a matter of fact, this phenomenon, will absolutely affect the angle and curvature of the bend, for such reason it must be taken into consideration in order to manufacture sheet metal parts bent within acceptable tolerance limits. However, the value of this springback is influenced by a multiplicity of process parameters, such as the thickness of the sheet, the hold time of the bending operation, the material properties and last but not least the depth of strike of the tool. In this paper, we have developed a model for predicting springback in the air V-bending process using the design of experiments method. Four three-level factors were considered in order to model springback in using the response surface method (RSM). The experimental tests were carefully carried out on a HACO press brake and on aluminum, ordinary steel and stainless steel specimens with different thicknesses. The in-depth study of the response surfaces to the different tests with the method of analysis of variance (ANOVA), allowed us to determine a robust empirical model linking the springback to the variables of the study. In addition, several relevant numerical simulations using the finite element method (FEM) with software (Abaqus) were performed to predict the evolution of springback when varying the parameters in the field of design of experiments. In fact, the comparison of the values predicted by the two approaches shows a satisfactory agreement.
Operations Research
Saeed Khalili; Masood Mosadegh Khah
Abstract
This study presents a new mathematical optimization model using queuing theory to determine the hotel capacity in an optimal manner. For this purpose, a Knapsack model based on the queuing theory is proposed. In this regard, after simulating a hotel's reception system with the help of queuing models ...
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This study presents a new mathematical optimization model using queuing theory to determine the hotel capacity in an optimal manner. For this purpose, a Knapsack model based on the queuing theory is proposed. In this regard, after simulating a hotel's reception system with the help of queuing models and using a limited two-dimensional Knapsack model, the capacity and an optimum number of rooms are obtained. Since the proposed model is too complex on large scales, a modified Genetic Algorithm (GA) approach enhanced by Taguchi method is employed to solve the problem. The obtained results indicate that unlike previous studies, the proposed models can be applied to different scenarios.
Operations Research
Fouad El-Hosiny; Mohamed Abdeldayem AbdelKhalek; Khaled Selim; Inge Osama
Abstract
An Electro-flotation cell was designed for industrial wastewater treatment. The affecting parameters of the Electro-flotation process such as, pH, initial dye concentration, temperature, current density, current type, ionic strength, stirring speed and number, connection and inter-distance of electrodes ...
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An Electro-flotation cell was designed for industrial wastewater treatment. The affecting parameters of the Electro-flotation process such as, pH, initial dye concentration, temperature, current density, current type, ionic strength, stirring speed and number, connection and inter-distance of electrodes were investigated using a synthetic Acid Red 1 (anionic), Basic Violet 3 (cationic) and Disperse Blue 14 (nonionic) dyes. Two textile wastewater samples were employed for performance evaluation. The maximum removal for all dyes is achieved at pH 7. The AC current and the bipolar electrodes were preferred. The maximum removal was achieved with AC current density of 80 A/m2 at 5 Volts through a bipolar connection of 8 electrode with 2 cm inter-distance. The designed Electro-flotation cell could remove 91.7 – 98.9 % of constituents of textile wastewater samples. The energy consumption was 1.39 Kwh/m3 of the treated wastewater.
Fuzzy optimization
Ranjan Kumar; Sripati Jha; Ramayan Singh
Abstract
In traditional shortest path problem it is always determined that the parameters (Time, Cost and Distance etc.) are fixed between different nodes. But in real life situations where uncertain parameters exist, parameters are considered as fuzzy numbers. In this paper, we explained the application ...
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In traditional shortest path problem it is always determined that the parameters (Time, Cost and Distance etc.) are fixed between different nodes. But in real life situations where uncertain parameters exist, parameters are considered as fuzzy numbers. In this paper, we explained the application scope of the given fuzzy ranking function. Using this method we can determine both the fuzzy shortest path and fuzzy shortest Distance from origin to Destination.
