A Method for Solving Fuzzy Transportation Problem
The most important and successful applications in the optimization refers to transportation problem. The main aspect of this paper is to find the least transportation cost of some commodities through a capacitated network when supply and demand of nodes and capacity and cost of edges are represented as fuzzy numbers. Here, we are solving the transportation problem using the Robust ranking technique, where fuzzy demand and supply are in the form of trapezoidal fuzzy numbers. The fuzzification of the cost of the transportation problem is discussed with the help of a numerical example.
Reliability Measures of Hybrid Electric Vehicles (HEVs) and Plug in Hybrid Electric Vehicles (PHEVs)
This study deals with the analysis of availability and reliability of hybrid electric vehicles (System 1) and plug-in hybrid electric vehicles (System 2). The purpose of this study is to find out the opinion of consumers who can afford their own hybrid car. The distribution of failure and repair rates is assumed to be exponential. A method of linear differential equations (LDE) is used to estimate reliability metrics such as average system failure and steady-state availability. Some special cases were evaluated using different values of the failure rates. In addition, we examined how the failure rate affected the system performance measures and we demonstrated the basic involved concept by comparing the results of both systems. The results are also presented graphically using MATLAB software.
Queuing for Success: A Quick Look at Service Optimization
This comprehensive review explores the application of queuing theory in optimizing service systems across diverse sectors. The studies analyzed delve into the intricacies of minimizing customer wait times and maximizing server utilization. Spanning from Fair Price Shops, banks, and post offices to supermarkets, healthcare centers, and petrol stations, the research employs various queuing models such as M/M/C, GI/M/c, and GI/M/1/N. Methodologies encompass case studies, simulation modeling, and mathematical analysis, providing insights into factors influencing service efficiency and customer satisfaction. Findings underscore the versatility and effectiveness of queuing theory, suggesting avenues for future research, including advanced queuing models, real-time analytics, and the integration of emerging technologies. Practical implementation in real-world service environments remains crucial for continuous improvement.
