Sheik Meeran

TL;DR: A subclass of the deterministic job-shop scheduling problem in which the objective is minimising makespan is sought, by providing an overview of the history, the techniques used and the researchers involved.

TL;DR: A non-systematic review of the theory and the practice of forecasting, offering a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts.

TL;DR: An experimental system for feature recognition from 2D drawings that has been designed to meet the automated process-planning requirements of today rather than tomorrow, and it has been demonstrated on a range of simple prismatic machined parts.

TL;DR: Major contributions in solving PiG using a Hopfield neural network, as well as applications of back-error propagation to general scheduling problems are presented.

TL;DR: The hybrid model proposed here surpasses most similar systems in solving many more traditional benchmark problems and real-life problems and achieves by the combined impact of several small but important features such as powerful chromosome representation, effective genetic operators, restricted neighbourhood strategies and efficient search strategies along with innovative initial solutions.