Four Methods for Maintenance Scheduling

Burke, Edmund K.; Clarke, Jo; Smith, A.

doi:10.1007/978-3-7091-6492-1_58

Cited by 13 publications

(15 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, several effective and efficient techniques have been suggested as alternatives to traditional optimisation-based techniques where the problem size is large and the exact optimal solution is not available. The modern techniques include simulated annealing [5,47,71], genetic algorithms [20,21,56,78,85], heuristics [35,51,77], memetics [8], and hybrids [6,49,50]. Various optimisation studies have also been conducted, including by Billinton and colleague [9], Charles-Owaba [13], Christiaanse [15], El-Sharkh [28], Pan [69], Yamayee and associate [86], and Zunn and Quintana [91,92].…”

Section: Important Fields Of Msmentioning

confidence: 99%

“…The major efforts, perhaps, are those that have been devoted to studying the traditional optimisation-based techniques such as integer programming [1,2,5,6,22], dynamic programming [5,6,9,10] and branch-and-bound [10,15,16,27] which have been proposed to solve small problems. These methods give an exact optimal solution.…”

Section: Important Fields Of Msmentioning

confidence: 99%

“…These methods give an exact optimal solution. A second type of research deals with several modern heuristic methods, including simulated annealing (SA) [71], genetic algorithm (GAs) [5,20,21,78], tabu search [5], and hybrid GAs (HGAs).…”

Section: Important Fields Of Msmentioning

confidence: 99%

See 2 more Smart Citations

Maintenance Scheduling: Description, Status and Future Directions

Oke

2012

The South African Journal of Industrial Engineering

View full text Add to dashboard Cite

In the past several decades, there have been diverse and significant research activities on maintenance scheduling (MS) due to the multi-disciplinary dimension of the field. As a consequence of this diversity and multi-disciplinary involvement, the MS literature is at present fragmented, somewhat misleading, and deficient in informative articles that cover the length, breadth, and depth of scientific investigations in the field. This paper reviews the scientific discipline of MS, covering general surveys, models, and significant empirical studies and cases in MS research. The research reflects the multidisciplinary nature of work in the field and suggests areas for future investigation. OPSOMMINGIn die afgelope aantal dekades was daar uiteenlopende en aansienlike navorsingsbedrywigheid op die gebied van instandhoudingskedulering (IS) weens die multidissiplinêre dimensie van die gebied. As gevolg van hierdie diversiteit en multidissiplinêre betrokkenheid is die ISliteratuur tans gefragmenteer, ietwat misleidend en gebrekkig aan insiggewende artikels wat die lengte, breedte en diepte van wetenskaplike ondersoeke op die gebied dek. Hierdie artikel bied 'n oorsig oor die wetenskaplike vakgebied van IS en dek algemene opnames, modelle en aansienlike empiriese ondersoeke en gevalle in IS-navorsing. Die navorsing weerspieël die multidissiplinêre uitkyk van werk op dié gebied en open gebiede vir toekomstige navorsing.

show abstract

Section: Important Fields Of Msmentioning

confidence: 99%

Section: Important Fields Of Msmentioning

confidence: 99%

See 1 more Smart Citation

Maintenance Scheduling: Description, Status and Future Directions

Oke

2012

The South African Journal of Industrial Engineering

View full text Add to dashboard Cite

show abstract

“…Several effective and sufficient techniques have been suggested as alternatives to traditional optimization-based techniques where the problem size is large and exact optimal solution is not available. The modern techniques include simulated annealing [59], genetic algorithms [7,10,20,65,71], heuristics [62], memetics [9], and hybrids.…”

Section: Literature Reviewmentioning

confidence: 99%

An Inflation-Based Maintenance Scheduling Model

Oke

Charles-Owaba

2012

The South African Journal of Industrial Engineering

View full text Add to dashboard Cite

This paper attempts to extend an original Gantt-charting model for optimal maintenance scheduling of multiple facilities in multiple periods credited to CharlesOwaba. In particular, an inflationary factor is incorporated into the period-dependent cost function element of the model. Some computational experimentation on the new model is tested. This work is perhaps the first to advance the extension of the Optimal Gantt Charting (OGC) model in terms of inflation. The work presents a wealth of research opportunities and has at least the modest potential to evaluate maintenance scheduling theory into the ranks of major theories of maintenance. OPSOMMINGDie artikel poog om inflasie te akkommodeer binne die raamwerk van 'n Ganttkaartmodel vir die bepaling van optimum skedulering van instandhouding vir meervoudige fasiliteite met die verloop van tyd. Inflasie vorm dus deel van die koste-element van die model. Die model is ook op 'n beperkte wyse gevalideer met behulp van 'n rekenaarstudie. Die verkreë resultate toon dat addisionele navorsing gedoen kan word om sodoende die metode te vestig in die voorste rang van instandhoudingsbeplanning

show abstract

“…Although SA has been adopted a number of times in the GMS literature, we could find no reference to experimentation with respect to improving the SA algorithm's effectiveness in the GMS context -a single cooling schedule (geometric) and a single elementary neighbourhood move operator (a random unit's maintenance starting time is changed to a random new time) are utilised throughout the literature [1][2][3][4][5][6][7]. In this paper, three adaptive cooling schedules and a new compound neighbourhood move operator are introduced in the context of GMS and compared to the schedules currently suggested in the literature.…”

Section: Introductionmentioning

confidence: 99%

An investigation into the effectiveness of simulated annealing as a solution approach for the generator maintenance scheduling problem

Schlünz

Vuuren

2013

International Journal of Electrical Power & Energy Systems

View full text Add to dashboard Cite

The generator maintenance scheduling (GMS) problem is the difficult combinatorial optimisation problem of finding a schedule for the planned maintenance outages of generating units in a power system. The GMS model considered in this paper is formulated as a mixed integer program, with a reliability optimality criterion, subject to a number of constraints. A new version of the simulated annealing (SA) method for solving the GMS problem is presented. Four cooling schedules (the geometric and three adaptive schedules), two neighbourhood move operators (an elementary move and an ejection chain move operator), and a hybrid local search heuristic/SA algorithm are compared. To our knowledge, this is the first study considering a different SA cooling schedule and move operator in a GMS context. A new 32-unit GMS test system is established and used in conjunction with a benchmark test system from the literature in this investigation. It is found that choosing a different cooling schedule and an ejection chain move operator yield improved results to that of the SA algorithm currently employed in the GMS literature. The hybrid SA algorithm performs very well compared to other methods on the benchmark test system from the literature, and an improved lower bound on the objective function value is presented for this test system.

show abstract

Four Methods for Maintenance Scheduling

Cited by 13 publications

References 9 publications

Maintenance Scheduling: Description, Status and Future Directions

Maintenance Scheduling: Description, Status and Future Directions

An Inflation-Based Maintenance Scheduling Model

An investigation into the effectiveness of simulated annealing as a solution approach for the generator maintenance scheduling problem

Contact Info

Product

Resources

About