Bi-objective optimization of maintenance scheduling for power systems

Hadjaissa, B.; Ameur, Khaled; Cheikh, Salah Med Ait; Essounbouli, Najib

doi:10.1007/s00170-015-8053-7

Cited by 11 publications

(5 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relevant stakeholders verified the results. Previous works such as by Denysiuk et al (2017), Hadjaissa et al (2016), Verma et al (2012), Masmoudi andHaït (2011), andCheung andHui (2002) are very limited to the specific equipment or focus on production or cost and do not take into account all maintenance jobs in MWM. Moreover, they do not incorporate such large number of constraints.…”

Section: Results Of the Proposed Toolmentioning

confidence: 99%

“…The literature in the maintenance scheduling and resource levelling is quite broad and Table 1 below highlights few of the works in this area. (Denysiuk et al, 2017) A multi-objective optimization model for optimizing maintenance schedules for pavements 2 (Hadjaissa et al, 2016) Methods to improve quality of energy production and reducing costs. Methods include mono-objective (make span), bi-objective (make span and training time) and modified genetic algorithm 3 (Verma et al, 2012) A non-dominated sorting genetic algorithm (NSGA-2) based multi-objective optimization approach for optimizing maintenance scheduling of machinery on ships 4 (Worrall and Mert, 1980) Dynamic decision rules for day-to-day scheduling in oil and gas sector, method to control backlog, and forecasting future work load 5 (Nurcahyo et al, 2019) Identification of key process areas in maintenance planning 6 (Jiu et al, 2013) Minimization of weighted sum of aversion of start time of maintenance, change over time, and train waiting time using mixed integer linear programming and hybrid genetic algorithm in coal industry.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Design Support Tool for Improving Maintenance Scheduling Process

Khalid

Soleymani

Sigsgaard

et al. 2020

Proc. Des. Soc.: Des. Conf.

View full text Add to dashboard Cite

The challenge of user requirements for maintenance scheduling design in large asset-intensive industries suffers from lack of academic and empirical studies. Therefore, using a representative case study, this paper aims to: (1) identify the current practices and complex scheduling requirements; (2) propose a design support tool to optimize the maintenance scheduling process; and (3) report the gained benefits. The results reveal that the proposed tool can decrease the resource requirements, increase the capacity utilization, and reduce the cost while addressing the complex user requirements.

show abstract

Section: Results Of the Proposed Toolmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Design Support Tool for Improving Maintenance Scheduling Process

Khalid

Soleymani

Sigsgaard

et al. 2020

Proc. Des. Soc.: Des. Conf.

View full text Add to dashboard Cite

show abstract

“…Existing metaheuristic algorithms are also being modified to improve their solving capabilities. A Modified Genetic Algorithm is utilized in [21] to solve a bi-objective optimization problem.…”

Section: B Existing Solution Methodsmentioning

confidence: 99%

A Tri-Objective Model for Generator Maintenance Scheduling

Moyo

Nwulu²,

Ekpenyong³

et al. 2021

IEEE Access

View full text Add to dashboard Cite

The complexity of power systems is increasing as new generating units are added to power systems in order to supply power to the growing economies. This has resulted in further research into the generator maintenance scheduling (GMS) problem which seeks to ensure optimal preventive maintenance scheduling that is effective and reliable. This research is focused on developing a generator maintenance schedule using a tri-objective model. The GMS tri-objective model is solved using two solution methodologies. The first is an exact solution method using mathematical modelling software, Advanced Interactive Multidimensional Modelling System (AIMMS). The second solution method is a recently developed metaheuristic algorithm called Exchange Market Algorithm (EMA). Results show that the tri-objective model finds a trade-off solution of the individual solution methods. The metaheuristic algorithm gives a better solution for larger optimization problems.

show abstract

“…Finally, changes to another EPA level causes major changes in the capacity and flexibility of staff in the department, but are difficult to include in the schedules due to the aggregation level of these schedules. For the lower EPA levels, tow scheduling (trainee and trainer) has to be applied, 895 Entrustable Professional Activities in Residency Programs -planning and scheduling issues while at higher EPA levels, single skilled operator scheduling would be possible (Hadjaissa, Ameur, Ait cheikh, & Essounbouli, 2016).…”

Section: Schedulers and Their Perceptions On The Residents' Schedulinmentioning

confidence: 99%

Entrustable Professional Activities in Residency Programs – planning and scheduling issues

Riezebos

Zee

Pruim

2019

5th International Conference on Higher Education Advances (HEAd'19)

View full text Add to dashboard Cite

Residency programs allow residents, i.e., graduate physicians, to qualify for being a specialist in one of the medical disciplines. Their educational programme is strongly focusing on competencies and skills, but will incur a major change in the near future in order to introduce Entrustable Professional Activities (EPA's). EPA's focus on actual physician tasks and are assessed by supervisors in the clinic. The trust levels indicate whether trainees are ready for the next milestone, such as unsupervised practice, based on assessment of performance of those activities. EPA's have not only effect on the internships and the assessment process, but also impact the planning and scheduling of the educational programmes, internships, patient care services, and cooperation between regional hospitals. This study examines the effect on the planning and scheduling process and proposes a framework for planning and scheduling in order to facilitate the organization of this type of educational programs. The main improvements have to be found in an improved regional coordination between the hospitals, a more leading role for the educational programme directors, and more intelligent planning and scheduling.

show abstract

Bi-objective optimization of maintenance scheduling for power systems

Cited by 11 publications

References 20 publications

A Design Support Tool for Improving Maintenance Scheduling Process

A Design Support Tool for Improving Maintenance Scheduling Process

A Tri-Objective Model for Generator Maintenance Scheduling

Entrustable Professional Activities in Residency Programs – planning and scheduling issues

Contact Info

Product

Resources

About