Single Machine Scheduling with Rejection

2012 ◽  
Vol 3 (2) ◽  
pp. 42-61 ◽  
Author(s):  
Atefeh Moghaddam ◽  
Lionel Amodeo ◽  
Farouk Yalaoui ◽  
Behrooz Karimi
Keyword(s):  
Single Machine ◽  
Optimization Problems ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Phase Method ◽  
Two Phase ◽  
General Technique ◽  
Combinatorial Optimization Problems ◽  
Traditional Research ◽  
The Cost

In this paper, the authors consider a single machine scheduling problem with rejection. In traditional research, it is assumed all jobs must be processed. However, in the real-world situation, certain jobs can be rejected. In this study, the jobs can be either accepted and scheduled or be rejected at the cost of a penalty. Two objective functions are considered simultaneously: (1) minimization of the sum of weighted completion times for the accepted jobs, and (2) minimization of the sum of penalties for the rejected jobs. The authors apply two-phase method (TPM), which is a general technique to solve bi-objective combinatorial optimization problems, to find all supported and non-supported solutions for small-sized problems. The authors present a mathematical model for implementing both phases. On the other hand, three different bi-objective simulated annealing algorithms have also been developed to find a good estimation of Pareto-optimal solutions for large-sized problems. Finally the authors discuss the results obtained from each of these algorithms.

SOLVING A SINGLE MACHINE SCHEDULING PROBLEM BY A DISCRETE VERSION OF ELECTROMAGNETISM-LIKE METHOD

2009 ◽  
Vol 18 (08) ◽  
pp. 1597-1608 ◽  
Author(s):  
NIKBAKHSH JAVADIAN ◽  
MOHSEN GOLALIKHANI ◽  
REZA TAVAKKOLI-MOGHADDAM
Keyword(s):  
Combinatorial Optimization ◽  
Single Machine ◽  
Optimization Problems ◽  
Continuous Optimization ◽  
Machine Scheduling ◽  
Population Based ◽  
Single Machine Scheduling ◽  
Discrete Version ◽  
Scheduling Problem ◽  
Combinatorial Optimization Problems

The electromagnetism-like method (EM) is a population based meta-heuristic algorithm utilizing an attraction-repulsion mechanism to move sample points (i.e., our solutions) towards the optimality. In general, the EM has been initially used for solving continuous optimization problems and could not be applied on combinatorial optimization ones. This paper proposes a discrete binary version of the EM for solving combinatorial optimization problems. To show the efficiency of our proposed EM, we solve a single machine scheduling problem and compare our computational results with the solutions reported in the literature. Finally, we conclude that our proposed method is capable of solving such well-known problems more efficiently than the previous studies.

scholarly journals Single-Machine Scheduling with Job Rejection, Deteriorating Effects, and Deteriorating Maintenance Activities

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Haiwei Nian ◽  
Zhizhong Mao
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Scheduling Problems ◽  
Job Rejection ◽  
Optimal Maintenance ◽  
Deterioration Effect ◽  
Maintenance Activities ◽  
The Cost ◽  
Rejection Penalty

This paper addresses the single-machine scheduling problems with simultaneous considerations of job rejection, deterioration effects, and deteriorating multimaintenance activities. A job is either rejected, in which case a rejection penalty has to be paid, or accepted and processed on the single machine. Three deterioration effect models are investigated, and it is assumed that each machine may be subject to several maintenance activities over the scheduling horizon, and the duration of the maintenance depends on its running time. Moreover, due to the restriction of the budget of maintenance, the upper bound of the total maintenance frequencies on the machine is assumed to be known in advance. The objective is to find jointly the optimal accepted job set, the optimal maintenance frequencies, the optimal maintenance positions, and the optimal accepted job sequence such that the cost function based on the total completion time and rejection penalty is minimized. It is shown that all the versions of the problem under study are polynomial time solutions.

Discrete Fireworks Algorithm for Single Machine Scheduling Problems

2016 ◽  
Vol 7 (3) ◽  
pp. 24-35 ◽  
Author(s):  
Mohamed Amine El Majdouli ◽  
Abdelhakim Ameur El Imrani
Keyword(s):  
Single Machine ◽  
Optimization Problems ◽  
Continuous Optimization ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Total Weighted Tardiness ◽  
Neighborhood Search ◽  
Scheduling Problems ◽  
Fireworks Algorithm ◽  
Machine Scheduling Problems

Over the recent years, Fireworks Algorithm has recorded an increasing success on solving continuous optimization problems, due to its efficiency, simplicity and more importantly its rapid convergence to good optimums. Thus, the Fireworks Algorithm performance is now widely comparable with the most popular methods in the optimization field such as evolutionary computation and swarm intelligence techniques. This paper introduces a discrete Fireworks Algorithm for combinatorial single machine scheduling problems. Taking advantage of the robust design of the original Fireworks Algorithm, a new adaptation of sparks generation is proposed with a novel use of the control parameters. To verify the explorative performance of the algorithm, a hybridization with Variable Neighborhood Search heuristic is implemented. To validate it, the proposed method is tested with several benchmarks instances of the single machine total weighted tardiness. A comparison with other optimization algorithms is also included. The obtained results exhibit the high performance of the proposed method.

scholarly journals Single machine scheduling with consideration of preventive maintenance and machine health

2018 ◽  
Vol 192 ◽  
pp. 01009 ◽  
Author(s):  
Kwei-Long Huang ◽  
Jakey Blue ◽  
Hao-Chen Weng ◽  
Shu-Han Liu
Keyword(s):  
Failure Rate ◽  
Single Machine ◽  
Preventive Maintenance ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Maintenance Cost ◽  
Health Index ◽  
Two Phase ◽  
Machine Failure ◽  
Machine Health

Because of Industry 4.0 and Internet of Things, it is easier to collect data from machines through sensors that are embedded inside machines. Once the status change of a machine is detected, production on that machine may need to be adjusted accordingly. In this research, we focus on single machine scheduling with considering the Preventive Maintenance (PM) and machine health index. Machine health index is categorized into three states: good, fair, and breakdown. When the machine moves from one state to another, the processing time of jobs will change as well as the machine failure rate. We develop a model to determine an optimal interval of performing PM and production sequence of jobs. A two-phase heuristic method is proposed to solve a large-size problem. Through different parameter settings, such as the machine failure rate, number of jobs, repair and maintenance cost, we show that the two-phase heuristic can obtain a solution with high quality.

scholarly journals Price of fairness in two-agent single-machine scheduling problems

2019 ◽  
Vol 276 (1) ◽  
pp. 79-87 ◽  
Author(s):  
Alessandro Agnetis ◽  
Bo Chen ◽  
Gaia Nicosia ◽  
Andrea Pacifici
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Scheduling Problems ◽  
Machine Scheduling Problems
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