Reliability estimation using an integrated support vector regression – variable neighborhood search model

© 2019 Elsevier Inc. As failure and reliability predictions play a significant role in production systems they have caught the attention of researchers. In this study, Support Vector Regression (SVR), which is known as a powerful neural network method, is developed as a way of forecasting reliability. Generally, SVR is applied in many research environments, and the results illustrate that SVR is a successful method in solving non-linear regression problems. However, SVR parameters tuning is a vital task for performing an accurate reliability estimation. We propose variable neighborhood search (VNS) for continuous space, including some simple but efficient shaking and local search as its main operators, to tune the SVR parameters and create a novel SVR-VNS hybrid system to improve the reliability of estimation accuracy. The proposed method is validated with a benchmark from the former literature and compared with conventional techniques, namely RBF (Gaussian), AR (autoregressive), MLP (logistic), MLP (Gaussian), and SVMG (SVM with genetic algorithm). The experimental results indicate that the proposed model has a superior performance for prediction reliability than other techniques

Sustainable open vehicle routing with release-time and time-window: a two-echelon distribution system

In an increasingly competitive economic environment, outsourcing for logistics has emerged as a cost-efficient strategy during freight transportation. The open vehicle routing problem is a type of classical vehicle routing problem, in which businesses outsource logistics to a third-party company and the vehicles do not return to the depot at the end of their journey. This paper develops a mixed integer linear programming model for two-echelon open vehicle routing problem that integrates city distribution constraints such as time-window and release-time. The release-time refers to the time at which products become ready at satellites for downstream distribution, and it is influenced by limited available resources and work load of each satellite. The proposed model determines the optimal configuration of the routes while minimizing the handling costs, penalty costs, and transportation costs. We use a comprehensive emission model that accounts for load, distance, speed and vehicle characteristics to estimate fuel consumption. Finally, we utilize a numerical example to illustrate the proposed model and explore the effects of release-time on total cost

Sustainable open vehicle routing with release-time and time-window: A two-echelon distribution system

In an increasingly competitive economic environment, outsourcing for logistics has emerged as a cost-efficient strategy during freight transportation. The open vehicle routing problem is a type of classical vehicle routing problem, in which businesses outsource logistics to a third-party company and the vehicles do not return to the depot at the end of their journey. This paper develops a mixed integer linear programming model for two-echelon open vehicle routing problem that integrates city distribution constraints such as time-window and release-time. The release-time refers to the time at which products become ready at satellites for downstream distribution, and it is influenced by limited available resources and work load of each satellite. The proposed model determines the optimal configuration of the routes while minimizing the handling costs, penalty costs, and transportation costs. We use a comprehensive emission model that accounts for load, distance, speed and vehicle characteristics to estimate fuel consumption. Finally, we utilize a numerical example to illustrate the proposed model and explore the effects of release-time on total cost

Feasibility study for developing an Indigenous branded range of beef products and services (Producer Innovation Fast-track)

Western Kangoulu Indigenous Group, University of Southern Queensland (USQ) and Meat & Livestock Australia (MLA) through the MLA Donor Company (MDC) are examining the desirability, feasibility and commercial viability of Indigenous branded beef products and services. The research included assessing the opportunities for new beef products branded as ‘Blackfella Beef’ and the alignment with Indigenous culture, business development and employment across the whole value chain. This research was funded by the producer innovation fast track program. An integral component of the ‘Blackfella Beef’ vision is to provide support and employment opportunities to the Indigenous communities involved with the ‘Blackfella Beef’ enterprise. This support will come in terms of skills development, employment, infrastructure and improvements to the genetics of Indigenous beef herds. The ‘Blackfella Beef’ project is working with existing organisations and programmes to leverage project resources, to utilise existing services where appropriate and useful and to develop new and innovative approaches where necessary and possible. The project have identified processing 2000 cattle per annum will deliver an initial $4M sales opportunity for ‘Blackfella Beef’