Optimal Control Algorithms and Their Analysis for Short-Term Scheduling in Manufacturing Systems

International audienceCurrent literature presents optimal control computational algorithms with regard to state, control, and conjunctive variable spaces. This paper first analyses the advantages and limitations of different optimal control computational methods and algorithms which can be used for short-term scheduling. Second, it develops an optimal control computational algorithm that allows for the solution of short-term scheduling in an optimal manner. Moreover, qualitative and quantitative analysis of the manufacturing system scheduling problem is presented. Results highlight computer experiments with a scheduling software prototype as well as potential future research avenues

Optimal control strategies for single-machine family scheduling with sequence-dependent batch setup and controllable processing times

The problem of scheduling jobs on an unreliable single machine is considered in this paper. The scheduling problem is characterized by the following features: jobs are grouped into classes of equivalent jobs; the generalized due date model is adopted for each class of jobs; it is possible to reduce the processing time of a job, at the price of the payment of an extra cost; a costly setup is required when switching between jobs of different classes. The scheduling problem is solved from a perspective which is different from the traditional determination of an optimal sequence of jobs; in fact, the objective of the paper is to determine optimal control strategies (functions of the system state) which allow generating the optimal decisions during the evolution of the system, taking into account the actual system state. In this way, optimal decisions can be promptly taken also in the presence of perturbations which affect the single machine (such as breakdowns and slowdowns). To this aim, a specific optimal control problem is stated and solved in the paper

Serial-batch scheduling – the special case of laser-cutting machines

The dissertation deals with a problem in the field of short-term production planning, namely the scheduling of laser-cutting machines. The object of decision is the grouping of production orders (batching) and the sequencing of these order groups on one or more machines (scheduling). This problem is also known in the literature as "batch scheduling problem" and belongs to the class of combinatorial optimization problems due to the interdependencies between the batching and the scheduling decisions. The concepts and methods used are mainly from production planning, operations research and machine learning

Algorithms for Scheduling Problems

This edited book presents new results in the area of algorithm development for different types of scheduling problems. In eleven chapters, algorithms for single machine problems, flow-shop and job-shop scheduling problems (including their hybrid (flexible) variants), the resource-constrained project scheduling problem, scheduling problems in complex manufacturing systems and supply chains, and workflow scheduling problems are given. The chapters address such subjects as insertion heuristics for energy-efficient scheduling, the re-scheduling of train traffic in real time, control algorithms for short-term scheduling in manufacturing systems, bi-objective optimization of tortilla production, scheduling problems with uncertain (interval) processing times, workflow scheduling for digital signal processor (DSP) clusters, and many more