Single Machine Predictive Scheduling Using Inserted Idle Times

Hongli Zhu,Hong Zhou

doi:10.1155/2014/304808

Abstract

A single machine predictive scheduling problem is considered. The primary objective is to minimize the total completion times. The predictability of the schedule is measured by the completion time deviations between the predictive schedule and realized schedule. The surrogate measure of predictability is chosen to evaluate the completion time deviations. Both of the primary objective and predictability are optimized. In order to absorb the effects of disruptions, the predictive schedule is generated by inserting idle times. Right-shift rescheduling method is used as the rescheduling strategy. Three methods are designed to construct predictive schedules. The computational experiments show that these algorithms provide high predictability with minor sacrifices in shop performance.

Highlights

Production scheduling is a decision making process which is related to the allocation of resources to tasks on machines for optimization of one or more scheduling objectives [1, 2]
Let Sp0 be a predictive schedule to minimize the primary objective without machine breakdowns and let Spp be a predictive schedule by inserting idle times
We address a single machine predictive scheduling using idle times

Summary

Introduction

Production scheduling is a decision making process which is related to the allocation of resources to tasks on machines for optimization of one or more scheduling objectives [1, 2]. In real cases, disruptions are inherently existent in every manufacturing environment Examples of such disruptions include machine breakdowns, new job arrivals, rush job arrivals, jobs cancellation, processing time changes, due date changes, and unavailability of raw materials or tools. In order to absorb the machine breakdown disruptions’ effects, a predictive schedule is generated in advance by inserting idle times in the practical production system [11,12,13]. O’Donovan et al [10] considered a predictive scheduling problem of a single machine to minimize total tardiness with stochastic machine breakdowns. Liu et al [8] considered a predictive scheduling of a single machine to minimize the total weighted tardiness with machine breakdowns They provided a two-stage multipopulation genetic algorithm.

Problem Formulation and Notations

Preliminaries

Heuristic Predictive Scheduling Methods

Experimental Results

B2 B3 B4 B5 B6

Conclusions