Approximation Algorithms for Multitasking Scheduling Problems

Feifeng Zheng,Ming Liu,Zhaojie Wang,Chengbin Chu

doi:10.1109/access.2020.3007755

Abstract

In this work, we incorporate human factors and real-life operations into newly proposed multitasking scheduling problems with periodic shift activities. It is motivated by personnel resource scheduling with periodic work shifts under the requirement of providing continuous service to customers. We model the problem as two identical parallel machine scheduling with complementary non-available time periods, and consider two models with the objectives of the makespan, i.e. the maximum completion time and respectively the total completion time. We then prove that the Greedy algorithm and SPT rule are of asymptotic and parametric approximation ratios for the two models, respectively.

Highlights

In many scheduling applications, human resources are becoming one of the critical factors or even the main issues in person-involved scheduling scenarios
We are inspired by the observation that several persons or work groups may own one shared machine resource. Some of such applications are long distance transportation by truck, medical teams for outpatient and emergencies, etc
Motivated by the above applications, we incorporate multitasking into parallel machine problem with periodic available time, and design approximation algorithms for different objectives

Summary

INTRODUCTION

Human resources are becoming one of the critical factors or even the main issues in person-involved scheduling scenarios. We are inspired by the observation that several persons or work groups may own one shared machine resource Some of such applications are long distance transportation by truck (drivers can be regarded as parallel machines, and the total mileage can be divided into n sections, which can be regarded as n jobs), medical teams for outpatient and emergencies (medical teams for outpatient and emergencies can be regarded as parallel machines, and patients can be regarded as jobs), etc. Our main contributions are proving that the Greedy algorithm and SPT rule are of asymptotic and parametric approximation ratios for the two models, respectively. This is of great significance to the multitasking scheduling problem when the number of jobs is large enough

LITERATURE REVIEW

THE MODEL OF MAKESPAN

THE MODEL OF TOTAL COMPLETION TIME

DISCUSSION

CONCLUSION