Nowadays, the internationalization of supply chains makes the management of operation affairs face a great challenge. On the other hand, vague parameters have challenged decision-makers to drive decision-making. To cope with these challenges, this study tries to model a green SCM (GSCM) model which considers fuzzy parameters. The objective function of our model is to minimize total fuzzy cost including fuzzy establishment costs of the plants and distribution centers, fuzzy transportation costs among the suppliers, facilities, and customers, fuzzy hiring cost of the transportation facilities, and miscellaneous fuzzy environmental impact costs. The developed model also includes facilities location constraints, material flow constraints, open transportation routing from plants to customers and from distribution centers to customers. Also, determining alternative products for customers has not been addressed in the literature. Therefore, this paper tries to focus on the mentioned complex problem and develop a comprehensive model. Because of the level of complexity of the developed model, two empowered meta-heuristic approaches, named fuzzy hybrid genetic algorithm (FHGA) and fuzzy hybrid biogeography-based optimization algorithm (FHBBO), are implemented to solve the NP-hard developed problem. According to the best of our knowledge, the proposed FHGA is not addressed in the literature in this way. For instance, most of the fuzzy algorithms either are not hybrid or get out of the fuzzy environment in one of their complex evolution processes. However, our fuzzy hybrid algorithms follow a fuzzy environment from beginning test initialization to calculating the objective function and presenting the convergence plots and none of our parameters are defuzzied in all steps of these processes. Besides, miscellaneous Figures, illustrations, and tables support the explanations of results.

In the scope of center location problem, transfer point location problems (TPLP) are the ones which have been studied more recently to make models more applicable in real world. The contribution of this work is to develop a model in which demand points are weighted and have a normal distribution. As an assumption, there is no transformation directly from a demand point to the service facility location. This means that the transfer point is always engaged. The contribution of work is summarized in two models. In the first model, all the points are considered in an area while in the second one the points are considered in several areas. The problem is to find out the best location for the transfer point so that the maximum expected weighted distance to all demand points through the transfer point is minimized. A mathematical solution is employed when demand points follow normal distribution, with some points of demands being in regions. Then, this model was solved by replacing real number in a real condition. We used Maple software to solve this objective function as well as MATLAB software to solve this model numerically.

This paper describes the investigation of different reliability measures of a complex system consisting of two subsystems with controllers in a series configuration, which is a useful opportunity for specific design problems. Subsystem-1 consisting n units functioning under the policy k-out-of-n: G; policy, and subsystem-2 has m units and operating under r-out-of-m: G; policy. The system failure rates of both subsystems are constant and assumed to obey an exponential distribution; two types of distribution are allowed to repair: general distribution and Gumbel-Hougaard family copula distribution. The system's partially failed states/ completely failed states are repaired using General/ copula distribution. After repair, the units in both the subsystems are good as new. The controller control both subsystems and the failure of controllers brings the subsystem in the complete failed state. The operator may fail the system deliberately if not satisfied with the organization. The system is analyzed employing the supplementary variable technique, and Laplace transforms implications and traditional system reliability measures, such as the system's availability, system reliability, and profit analysis, have been computed for particular values of failure and repair parameters.

The main aim of this research is to find the best inventory review policy for different types of items in group B in ABC analysis through minimizing the total cost of the system and maximizing the service level. Moreover, this study has considered several operational constraints such as limitations on storage space, number of orders, and allowable shortage. To solve this problem, first, an individual optimization method is utilized to obtain optimal solutions. Then, two classic and novel multi-objective optimization methods have been used to convert the bi-objective problem to a single-objective and reach the near-optimal solutions for both objectives simultaneously. Finally, the proposed methods are compared in terms of objective function values and computational time to find the better method.

The healthcare sector is one of the largest service industries with the highest potential to improve environmental performance. Hospitals as an important part of the healthcare system must act in a way that reduces their environmental consequences, which requires having a green supplier. The aim of this study was to identify the effective factors on the green supplier selection (GSS) in the hospital and to present an excellent model for analyzing the relationships between these factors. In this study, 14 concepts that effect the green supplier selection of a hospital have been extracted from in-depth literature and interviews entailing: financial capability, creativity and innovation, green technology, flexibility, organizational capability, commitment, trust on supplier, green quality, green transportation, environmental cooperation with customers, hazardous materials management, buy green, green warehouse and green packaging.In addition Intuitive fuzzy cognitive mapping approach was also used for data analysis and conclusion. The results showed that green technology index with 0.43 degree was the most influential and organizational capability index with 0.29 degree had the most influence over the other concepts. In addition, focusing on concepts like financial capability, trust on supplier and creativity and innovation process of green supplier selection of hospital. Taking these in consideration these factors should be given specific attention.

Ethiopia's industrial development strategy is characterized by manufacturing-led and expansion labor-intensive industrialization. The country expects to generate more income from the exported market. However, the case company is still known not to become productive as much as possible due to different reasons. One of the big challenges of the company has the problem with holding inappropriate inventory and with determines their optimal cost due to poor production planning. So that to solve this problem objective of the paper is to minimize total cost through the integration of seasonal forecasting and integer programming model without violating demand fulfillments. This technique improves resource utilization and enhances inventory control or stock control system. Currently, the company produces different kinds of products grouped into four common types of products (knitted garment, knitted fabric, woven garment, and woven fabric). The data survey system was both primary and secondary system and classified the products using A B C (always better classification) classification. The optimal solution was settled through the integration of seasonal forecasting and integer programming. As the Sensitivity analysis indicated the a big gap between production capacity and actual demand of the products. As the optimized solution indicated that total cost of production cost and inventory cost was minimized and the optimal production plan as well safety stock levels in each quarter was settled. Seasonal demand forecasting is a key activity for a garment which more or less controls all activities of production processes since garment products are affected by seasonal. As the result and discussion have shown that after optimized increase profit of the company through minimizing production cost and inventory costs since both costs are the big constraint of the company. Based on the optimized solution finding annually total cost needs for each A, B, and C – categories products are 57,225,920 BIRR 4,733,013 BIRR, 8,229,309 BIRR, respectively for production and inventory costs. The optimized solution indicated that if the company implemented exactly the proposed solution it will get an additional,4,219,788.8 BIRR,772,055.8 BIRR,2,119,824.2 BIRR respectively for A, B, C categories products totally around 7,111,668.8 BIRR profit per year will get. To end, it was concluded that this remarkable profit increment of the case company can certainly enhance its productivity and worldwide competitiveness. This research will create further pathways for other researchers to accomplish substantial studies on other garment sectors or other manufacturing industries based on local and international perspectives.

In developing countries, whereas the urban bus network is a major part of public transportation system, it is necessary to try to find the best design and routing for bus network. Optimum design of school bus routes is very important. Non-optimal solutions for this problem may increase traveling time, fuel consumption, and depreciation rate of the fleet. A new bus routing problem is presented in this study. A multi-objective mixed integer model is proposed to handle the associated problem. Minimization of transportation cost as well as traveling time is the main objectives. The main contributions of this paper are considering gender separation as well as mixed-loading properties in the school bus routing problem. Moreover, special and handicapped students are considered in this problem. The proposed model is applied in a real case study including 4 schools in Tehran. The results indicate the efficiency of the proposed model in comparison with the existing system. This comparison shows that the students’ travelling time is reduced by 28% for Peyvand middle smart school, 24% for Tehran international school, 13% for Hemmat School and 21% for Nikan High school. A customized Genetic Algorithm (GA) is proposed to solve the model. Penalty functions are used to handle the several constraints of the problem in Genetic Algorithm. The results justify the applicability and efficacy of the both proposed model and solution approach.

This paper deals with the service performance analysis and improvement using discrete event simulation has been used. The simulation of the health care has been done by arena master development 14-version software. The performance measurement for this study are patients output, service rate, service efficiency and it is directly related to waiting time of patients in each service station, work in progress, resource utilization. Simulation model was building for Bahir Dar clinic and then, prepared the proposed model for the system. Based on the simulation model run result, the output of the existing healthcare service system is low due to presence of bottlenecks on the service system. Moreover, the station with the largest queue and high resource utilization are identified as a bottleneck. The bottlenecks, which have identified are reduced by using reassigning the existing resources and add new resources and merging the similar services, which has under low resource utilization (nurses). Finally, the researchers have proposed a developed model from different scenarios. Moreover, the best scenario is developed by combining scenario 2 and 3. And then, service efficiency of the healthcare has increased by 9.86 percent, the work in progress (WIP) are reduced by 3 patients from the system and the service capacity of the system is increased 34 to 40 patients per day due to the reduction of bottleneck stations.

The current research has been conducted to provide a model for customer experience management in the mobile banking industry for customers of commercial banks in Dubai. An explorative mixed methods research (qualitative and quantitative) was used in the research. Data were gathered in both qualitative phase (based on grounded theory) and quantitative phase (based on cross-sectional survey method). In the qualitative phase, population consisted of academic specialists and experts (university professors in the field of management) selected by judgmental sampling method of snowball sampling type. Data were gathered using a semi-structured interview. Data gathering reached theoretical data saturation in the twenty-fifth interview, so interviews were stopped at this point. The results of coding based on grounded theory led to the identification of 170 open codes, 24 axial codes, and 7 selective codes including value, cognitive, motivational, sensory, physical, behavioral, and communicative ones. In the quantitative phase, population consisted of 100,000 users (equal numbers of men and women) of mobile banking services. Given that the community variance was not available, Morgan and Krejcie table were used to determine the sample size that was calculated at 384 individuals. Data analysis in the quantitative phase confirmed the findings of qualitative research according to chi-square (x2), goodness of fit (GFI), adjusted goodness of fit (AGFI), and root mean squared error of approximation (RMSEA) indices.

The wind turbine has grown out to be one of the most common Renewable Energy Sources (RES) around the world in recent years. This study was intended to position the Wind Turbine (WT) on a wind farm to achieve the highest performance possible in Electric Distribution Network (EDN). In this paper a new optimization algorithm namely Salp Swarm Algorithm (SSA) is applied to solve the problem of optimal integration of Distributed Generation (DG) based WT (location and sizing) in EDN. The proposed algorithm is applied on practical Algerian EDN in Constantine city 73-bus in presence single and multiple WT-DGs for reducing the total active power loss. The validity of the proposed algorithm is demonstrated by comparing the obtained results with those reported in literature using other optimization algorithms. A numerical simulation including comparative studies was presented to demonstrate the performance and applicability of the proposed algorithm.