Timed Supervisory Control for Operational Planning and Scheduling under Multiple Job Deadlines

TL;DR

This paper introduces a method for operational planning and scheduling that ensures multiple job deadlines are met or optimally relaxed using a time-weighted automaton framework and controllable sublanguage computations.

Contribution

It presents a novel approach to handle multiple deadlines in scheduling by computing supremal controllable sublanguages and minimal deadline relaxations within a time-weighted automaton model.

Findings

Successfully determines if all deadlines can be met.

Computes controllable sublanguages to minimize job earliness.

Identifies minimal deadline relaxations when deadlines are infeasible.

Abstract

In this paper, we model an operational planning and scheduling problem under multiple job deadlines in a time-weighted automaton framework. We first present a method to determine whether all given job specifications and deadlines can be met by computing a supremal controllable job satisfaction sublanguage. When this supremal sublanguage is not empty, we compute one of its controllable sublanguages that ensures the minimum total job earliness by adding proper delays. When this supremal sublanguage is empty, we will determine the minimal sets of job deadlines that need to be relaxed.