International Journal of Research in Industrial Engineering
Volume:7 Issue: 4, Autumn 2018

Doctor scheduling is a complex, costly and time-consuming exercise. This study develops a constraint satisfaction and penalty minimisation scheduling model for meeting ‘hard constraints’ and minimises the cost of violating ‘soft constraints’, i.e. the user inputs, the total number of doctors to be scheduled, the maximum penalty to be met, and the minimum number of doctors to be assigned per shift. The algorithm creates a schedule which checks against all the constraints. The total schedule penalty associated with the constraint violations should be less than or equal to the user input penalty. If this condition is met, the schedule gets produced as the final and near-optimal solution. The model is managed to create a near optimal schedule with the minimal rule violations. However, it is challenging to provide a schedule with no rule violations. Such a situation is shown by the amount of computational time required to create a zero-penalty schedule, hours or even days needed to create a zero-penalty schedule. The system creates a schedule for a short period (weekly schedule) to promote flexibility; however, such a system does not promote fairness. Fairness is achieved through a cyclic schedule with rotations equal to the total number of doctors being scheduled. The system is managed to create a streamlined and flexible working environment and helped to improve the quality of healthcare. An optimization protocol can be incorporated into the system to reduce the search space and get the best optimal schedule since it is possible to get many schedules under the same user-defined parameters.

Nowadays, the supply chain has become a buzzword in the business field. The only supply chain can help to lead a business in an organized way. However, in a supermarket, the supply chain is very important, but they need to ensure better communication with the supplier, customer, and internal management too. Each factor of the supply chain has a good effect on itself. The purpose of this research is to explore the important supermarket supply chain factors found in the literature and from supply chain experts and to develop a framework which can help to arrange the criteria in a sequence from most important to the worst by considering each sector of the supply chain. This paper has studied one of the supermarkets in Bangladesh, namely Save ‘n’ Safe. Authors have taken FAHP, one of the tools of MCDM, to figure it out the most effective factors. The result reveals that managing inventory, internal information sharing, and accurate demand forecasting are the most affected factors for the Save ‘n’ Safe (a supermarket). Finally, some recommendations have been given to improve the existing situation. This study can be used not only in the other supermarkets but also any other retail or grocery shops.

In the statistical process control when the process is very sensitive and control limit shifts are the prime concerns, there fuzzy control charts can be a better solution. In decision making, extra “rather in control” and “rather out of control” decisions facilitate to find out the slight changes in the control chart. The automation of fuzzy control chart in the Excel VBA makes the data input and decisions making process faster. The vagueness of the data is removed as the charts deal with the triangular or trapezoidal area rather than some points in the control limits. Alongside the fuzzy control charts, Marcucci approach has been followed to find out the goodness-of-fit of the samples and to find out the effectiveness of fuzzy control charts.

Although the development of science and technology in the present era has increased human satisfaction from life, it has caused the problems such as environmental pollution and increased demand for energy carriers, especially fossil fuels. Considering that fossil fuels can be exhausted, the most suitable solutions to address the consequences are the use of renewable energy sources to generate electricity. In this paper, using the Particle Cumulative Optimization (PSO) algorithm, we have tried to design an optimal photovoltaic and winding model to supply the power of an area in such a way that the electrical charge generated by this system has the reliable capability and economically viable.

Trend analysis of domestic air travel demand in Nigeria was examined based on yearly passenger demand from 2010 to 2017. Ordinary Least Square (OLS) regression was used to forecast for twelve years (2018 to 2030) demand for domestic air passenger travel in Nigeria. The demand for domestic air passenger in Nigeria from year 2010 to 2017 was compared with the forecast. There seems to be periods of fluctuations in the demand for domestic air passenger travel in Nigeria from year 2010 to 2017 which are expected to have effect on the forecast of domestic air travel. Calculation and computation reveals that the coefficient of determination R2 is 0.203 which signifies a high error term such that the explanation level is very low; hence the prediction or forecast is unreliable. Despite the decline in the forecast of domestic air passenger demand in the future, and the fact that the forecast is unreliable, hence inconclusive as shown from the coefficient of determination, government agencies should be sensitive to the forecast and try to adopt new policies and strategies that will improve the demand for domestic air passenger travel in Nigeria.

Internet of Things (IoT) technology is based on interconnected things in a dynamic and distributed environment. The IoT contains many widely pervasive and heterogeneous small things with limited storage, energy resources, and processing capacities. These limitations are an obstacle for developing IoT applications and involve challenging issues such as interoperability, scalability, performance, and availability. Cloud Computing is one of the promising approaches that can be integrated with IoT to overcome these limitations. The Cloud provides shared resources (network, storage, computing, and software) and is characterized by ubiquitous, low-cost, and virtualization features. This paper presents the Cloud-based IoT platform and describes the communication, processing, and storage properties of it. This platform can benefit from the resources and services of the Cloud to collect, transmit, analyze, process, and store the data generated by the heterogeneous things. We also represent the projects that have implemented the Cloud-based IoT platform.