scholarly journals Uniform Parallel-Machine Scheduling for Minimizing Total Resource Consumption With a Bounded Makespan

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 15791-15799 ◽  
Author(s):  
Shih-Wei Lin ◽  
Kuo-Ching Ying
Keyword(s):  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Resource Consumption ◽  
Uniform Parallel Machine Scheduling ◽  
Total Resource

scholarly journals Uniform Parallel Machine Scheduling with Dedicated Machines, Job Splitting and Setup Resources

2019 ◽  
Vol 11 (24) ◽  
pp. 7137 ◽  
Author(s):  
Jun-Ho Lee ◽  
Hoon Jang
Keyword(s):  
Mathematical Optimization ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Dedicated Machines ◽  
Job Splitting ◽  
Constructive Heuristic ◽  
Parallel Machine Scheduling Problem ◽  
Mathematical Optimization Model ◽  
Uniform Parallel Machine Scheduling

We examine a uniform parallel machine scheduling problem with dedicated machines, job splitting, and limited setup resources for makespan minimization. In this problem, machines have different processing speeds, and each job can only be processed at several designated machines. A job can be split into multiple sections and those sections can be processed on multiple machines simultaneously. Sequence-independent setup times are assumed, and setup operations between jobs require setup operators that are limited. For the problem, we first develop a mathematical optimization model and for large-sized problems a constructive heuristic algorithm is proposed. Finally, we show that the algorithm developed is efficient and provides good solutions by experiments with various scenarios.

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 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.

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