scholarly journals Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Li Sun ◽  
Bin Wu ◽  
Lei Ning
Keyword(s):  
Resource Allocation ◽  
Learning Effect ◽  
Waiting Times ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Absolute Deviation ◽  
Delivery Times ◽  
Completion Times ◽  
Total Resource

We investigate parallel-machine scheduling with past-sequence-dependent (p-s-d) delivery times, DeJong’s learning effect, rate-modifying activity, and resource allocation. Each machine has a rate-modifying activity. We consider two versions of the problem to minimize the sum of the total completion times, the total absolute deviation of job completion times, and the total resource allocation and the sum of the total waiting times, the total absolute deviation of job waiting times, and the total resource allocation, respectively. The problems under our present model can be solved in polynomial time.

scholarly journals Results of Parallel-Machine Scheduling Model with Maintenance Activity considering Time-Dependent Deterioration, Delivery Times, and Resource Allocation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Li Sun ◽  
Xiao-hong Zhang ◽  
Lei Ning
Keyword(s):  
Resource Allocation ◽  
Waiting Times ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Time Dependent ◽  
Absolute Deviation ◽  
Maintenance Activity ◽  
Delivery Times ◽  
Completion Times ◽  
Total Resource

This paper investigates parallel-machine scheduling models with maintenance activity, delivery times, time-dependent deterioration, and resource allocation. We consider two forms of the problem: the first is to minimize the sum of total completion times, total machine loads, the total absolute deviation of job completion times, and the total resource allocation; the second is to minimize the sum of total waiting times, total machine loads, the total absolute deviation of job waiting times, and the total resource allocation. The problems are proved to be solvable in polynomial time.

Parallel-Machine Scheduling with Delivery Times and Deteriorating Maintenance

2015 ◽  
Vol 32 (04) ◽  
pp. 1550029 ◽  
Author(s):  
Wei-Min Ma ◽  
Li Sun ◽  
S. C. Liu ◽  
T. H. Wu
Keyword(s):  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Absolute Deviation ◽  
Total Load ◽  
Delivery Times ◽  
Polynomial Time Algorithms ◽  
Deteriorating Maintenance ◽  
Time Required ◽  
Completion Times

In this paper, we consider parallel-machine scheduling with past-sequence-dependent (p-s-d) delivery times and deteriorating maintenance. The delivery time of a job is proportional to its waiting time in the system. Each machine has a deteriorating maintenance activity, i.e., delaying the maintenance increases the time required to perform it. We consider three versions of the problem to minimize the total absolute deviation of job completion times, the total load on all the machines, and the total completion time. We develop polynomial-time algorithms to solve them.

scholarly journals Uniform Parallel Machine Scheduling Problem with Controllable Delivery Times

2015 ◽  
Vol 3 (6) ◽  
pp. 525-537
Author(s):  
Kai Li ◽  
Hui Li ◽  
Bayi Cheng ◽  
Qing Luo
Keyword(s):  
Resource Allocation ◽  
Heuristic Algorithm ◽  
Large Scale ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Scheduling Problem ◽  
Delivery Times ◽  
Parallel Machine Scheduling Problem ◽  
Uniform Parallel Machine Scheduling

AbstractThis paper considers the uniform parallel machine scheduling problem with controllable delivery times, which assumes that the delivery times of jobs are linear decreasing functions of the consumed resource. It aims to minimize the maximum completion time under the constraint that the total resource consumption does not exceed a given limit. For this NP-hard problem, we propose a resource allocation algorithm, named RAA, according to the feasible solution of the uniform parallel machine scheduling problem with fixed delivery times. It proves that RAA algorithm can obtain the optimal resource allocation scheme for any given scheduling scheme inO(nlogn)time. Some algorithms based on heuristic algorithm LDT, heuristic algorithm LPDT and simulated annealing are proposed to solve the uniform parallel machine scheduling problem with controllable delivery times. The accuracy and efficiency of the proposed algorithms are tested based on those data with problem sizes varying from 40 to 200 jobs and 2 to 8 machines. The computational results indicate that the SA approach is promising and capable of solving large-scale problems in a reasonable time.

scholarly journals Parallel-Machine Scheduling Problems with Past-Sequence-Dependent Delivery Times and Aging Maintenance

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Wei-min Ma ◽  
Li Sun ◽  
Xue-qin Zeng ◽  
Lei Ning
Keyword(s):  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Polynomial Algorithms ◽  
Scheduling Problems ◽  
Absolute Deviation ◽  
Total Load ◽  
Delivery Times ◽  
Sequence Dependent ◽  
Machine Scheduling Problems

We consider parallel-machine scheduling problems with past-sequence-dependent (psd) delivery times and aging maintenance. The delivery time is proportional to the waiting time in the system. Each machine has an aging maintenance activity. We develop polynomial algorithms to three versions of the problem to minimize the total absolute deviation of job completion times, the total load, and the total completion time.

A Bicriteria Approach for Single Machine Scheduling with Resource Allocation, Learning Effect and a Deteriorating Maintenance Activity

2017 ◽  
Vol 34 (04) ◽  
pp. 1750011 ◽  
Author(s):  
Zhusong Liu ◽  
Zhenyou Wang ◽  
Yuan-Yuan Lu
Keyword(s):  
Resource Allocation ◽  
Single Machine ◽  
Learning Effect ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Maintenance Activity ◽  
Optimal Resource ◽  
Deteriorating Maintenance ◽  
Polynomially Solvable ◽  
Completion Times

This paper considers the single machine scheduling with learning effect, resource allocation and deteriorating maintenance activity simultaneously. For the convex resource allocation consumption function, we provide a bicriteria analysis where the first (schedule) criterion is to minimize the total weighted sum of makespan, total completion time and total absolute differences in completion times, and the second (resource) criterion is to minimize the total weighted resource consumption. Our aim is to find the optimal resource allocations and job sequence that minimize the three different models of considering the two criterion. We show that these three models are polynomially solvable respectively.

Unrelated Parallel-Machine Scheduling with Deteriorating Jobs and Rejection

2012 ◽  
Vol 263-266 ◽  
pp. 655-659 ◽  
Author(s):  
Chou Jung Hsu ◽  
Chia Wen Chang
Keyword(s):  
Completion Time ◽  
Deteriorating Jobs ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Unrelated Parallel Machine ◽  
Absolute Deviation ◽  
Total Load ◽  
Unrelated Parallel Machine Scheduling ◽  
Total Penalty

This paper aimed to investigate the unrelated parallel-machine scheduling with deteriorating jobs and rejection. The objective is to find the rejected jobs, the non-rejected jobs, and the optimal non-rejected job sequence so that the cost function that includes the weighted of total load, total completion time, and total absolute deviation of completion time plus the total penalty of the rejected jobs would be minimized. Results showed that the problem is polynomial time solvable when the number of machine is fixed.

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