Real-World Extensions To Scheduling Algorithms Based On Lagrangian Relaxation

Recently, efficient scheduling algorithms based on Lagrangian relaxation have been proposed for scheduling parallel machine systems and job shops. In this article, we develop real-world extensions to these scheduling methods. In the first part of the paper, we consider the problem of scheduling single operation jobs on parallel identical machines and extend the methodology to handle multiple classes of jobs, taking into account setup times and setup costs, The proposed methodology uses Lagrangian relaxation and simulated annealing in a hybrid framework, In the second part of the paper, we consider a Lagrangian relaxation based method for scheduling job shops and extend it to obtain a scheduling methodology for a real-world flexible manufacturing system with centralized material handling.

Robust controller for an autonomous small refrigeration unit

The authors describe the constructional features of a controller for operating an autonomous refrigeration unit powered by a field of photovoltaic panels and backed up by a generator set. The controller enables three voltage levels of operation of an inverter to meet the start, run and off cycle conditions of the refrigerator compressor. The algorithm considers several input and output parameters and status signals from each subsystem of the unit to deduce a control strategy. Such units find application for storage of vaccines and life-saving medicines requiring uninterrupted refrigeration, in medical shops, rural health centres, veterinary laboratories etc.