Minimizing the makespan in a single machine scheduling problems with flexible and periodic maintenance

Low, Chinyao; Ji, Min; Hsu, Chou-Jung; Su, Chwen-Tzeng

doi:10.1016/j.apm.2009.04.014

Cited by 112 publications

(47 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A mixed binary integer programming and heuristics to minimize the number of in-process jobs have been also proposed by Chen [15]. Finally, Low et al [16,17] surveyed the problem of single machine scheduling considering two alternative strategies, namely, machine unavailability after a fixed time period and also after processing a specific number of jobs to change the tool. They considered minimization of the makespan as their objective.…”

Section: Isrn Industrial Engineeringmentioning

confidence: 99%

A Dynamic Genetic Algorithm for Solving a Single Machine Scheduling Problem with Periodic Maintenance

Zade

Fakhrzad

2013

ISRN Industrial Engineering

View full text Add to dashboard Cite

The scheduling problem with nonresumable jobs and maintenance process is considered in order to minimize the makespan under two alternative strategies. The first strategy is to implement the maintenance process on the machine after a predetermined time period and the second one is to consider the maximum number of jobs that can be done with an especial tool. We propose a new mathematical formulation for the aforementioned problem which is included in the NP-Hard class of problems; in the second part of the paper, we propose a dynamic genetic algorithm so that the large-and medium-scale problems could be solvable in computationally reasonable time. Also we compare the performance of the proposed algorithm with existing methods in the literature. Experimental results showed that the proposed genetic algorithm is able to attain optimum solutions in most cases and also corroborate its better performance from the existing heuristic methods in the literature.

show abstract

Section: Isrn Industrial Engineeringmentioning

confidence: 99%

A Dynamic Genetic Algorithm for Solving a Single Machine Scheduling Problem with Periodic Maintenance

Zade

Fakhrzad

2013

ISRN Industrial Engineering

View full text Add to dashboard Cite

show abstract

“…As for the fourth group of the aforementioned problems, Low et al [15] considered the single-machine scheduling problem with exible periodic maintenance to minimize the makespan (i.e., 1; h i jfpajC max , where fpa stands for exible periodic activity/maintenance) and proposed a heuristic algorithm to address it.…”

Section: Introductionmentioning

confidence: 99%

Minimizing maximum earliness in single-machine scheduling with flexible maintenance time

2017

View full text Add to dashboard Cite

Abstract. We consider minimizing the maximum earliness in the single-machine scheduling problem with exible maintenance. In this problem, preemptive operations are not allowed, the machine should be shut down to perform maintenance, tool changing or resetting takes a constant time, and the time window inside which maintenance should be performed is prede ned. We show that the problem is NP-hard. Afterward, we propose some dominance properties and an e cient heuristic method to solve the problem. Also, we propose a branch-and-bound algorithm, in which our heuristic method, the lower bound, and the dominance properties are incorporated. The algorithm is computationally examined using 3,840 instances up to 14,000 jobs. The results impressively show that the proposed heuristic algorithm obtains the optimal solution in about 99.5% of the cases using an ordinary processor in a matter of seconds at most.

show abstract

“…Scheduling jobs under tool change considerations is quite common in many industrial environments such as Computer Numerically Controlled (CNC) work centers, Integrated Circuit (IC) testing operations and Printed Circuit Board (PCB) production (Low et al, 2010). Tool replacement operations in industrial applications may be motivated by part mix production (Tang & Denardo 1988;Hertz et al 1998), but the tool change issue induced by wear usually has a greater impact on production performances, as confirmed by Gray et al (1993) who stated that, in real-world applications, tool changes due to wear are approximately 10 times more frequent than those induced by job mix.…”

Section: Introductionmentioning

confidence: 99%

Minimizing the total tardiness for the tool change scheduling problem on parallel machines

Costa¹,

Cappadonna²,

Fichera³

2016

10.5267/j.ijiec

View full text Add to dashboard Cite

This paper deals with the total tardiness minimization problem in a parallel machines manufacturing environment where tool change operations have to be scheduled along with jobs. The mentioned issue belongs to the family of scheduling problems under deterministic machine availability restrictions. A new model that considers the effects of the tool wear on the quality characteristics of the worked product is proposed. Since no mathematical programming-based approach has been developed by literature so far, two distinct mixed integer linear programming models, able to schedule jobs as well as tool change activities along the provided production horizon, have been devised. The former is an adaptation of a well-known model presented by the relevant literature for the single machine scheduling problem with tool changes. The latter has been specifically developed for the issue at hand. After a theoretical analysis aimed at revealing the differences between the proposed mathematical models in terms of computational complexity, an extensive experimental campaign has been fulfilled to assess performances of the proposed methods under the CPU time viewpoint. Obtained results have been statistically analyzed through a properly arranged ANOVA analysis.

show abstract

Minimizing the makespan in a single machine scheduling problems with flexible and periodic maintenance

Cited by 112 publications

References 19 publications

A Dynamic Genetic Algorithm for Solving a Single Machine Scheduling Problem with Periodic Maintenance

A Dynamic Genetic Algorithm for Solving a Single Machine Scheduling Problem with Periodic Maintenance

Minimizing maximum earliness in single-machine scheduling with flexible maintenance time

Minimizing the total tardiness for the tool change scheduling problem on parallel machines

Contact Info

Product

Resources

About