A non-zero integer non-linear programming model for maintenance workforce sizing

Ighravwe, Desmond Eseoghene; Oke, Sunday Ayoola

doi:10.1016/j.ijpe.2014.01.004

Cited by 30 publications

(18 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…But certain efforts in studying logistical modelling in social business systems took place before. For example: modelling of the hiring process (Karsak, 2000); cost for labor resources' optimization (Matthews, 2004); scheduling staff's work (Topaloglu & Selim, 2010); increase in workers' productivity (Ighravwe & Oke, 2014) and so on. Meanwhile these studies are not focused on studying moral-psychological climate and complex estimation of socio-economic means concerning staff management improvement at enterprises.…”

Section: Literature Reviewmentioning

confidence: 99%

Logistical modelling of managerial decisions in social and marketing business systems

Velychko

2017

Journal of International Studies

View full text Add to dashboard Cite

Abstract. Logistical modelling of business systems within the context of mathematical logistics, logistical management, operational research as well as rationalistic provision of logistics at an enterprise have been considered in the article. The research was carried out on the methodological basis which included the authors' developments and implied conveying familiar knowledge on new objects within the field of linear programming. Scientific novelty concerns the development of categorical toolkit as well as the existing methodical approaches of rationalistic logistics to managerial decisions. Rational areas of using terms "logistical model" and "model of logistics" in business environment have been determined. The authors' methodology of constructing logistical models in management of separate social and marketing systems of enterprises according to minimization and maximization criteria is presented. Ways of using modelling at not conventional objects of logistical support for managerial decisions have been suggested in the context of studying the moral psychological climate of staff and complex estimation of socioeconomic measures of staff management improvement. The procedure of logistical optimization in the system of distributing and advertising activity of the enterprise has been developed. Approbation of the developed models has been carried out and possibilities for further model's complication by output data, variables, and limitations under specific practical conditions have been grounded.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Logistical modelling of managerial decisions in social and marketing business systems

Velychko

2017

Journal of International Studies

View full text Add to dashboard Cite

show abstract

“…From this prospective a number of articles were found focusing largely on technical matters, which include inventory optimisation [47], workforce sizing [25], failure investigation [42], maintenance policy [50], modelling [32], warranty modelling [44]. Other studies have incorporated economy in the conventions of their models [26,51].…”

Section: General Overviewmentioning

confidence: 99%

“…The positive and negative ideal solutions of the alternatives were determined using Eqs. (24) and (25). The results obtained were used to compute the alternatives closeness coefficients (Table 20).…”

Section: Case Studymentioning

confidence: 99%

A multi-hierarchical framework for ranking maintenance sustainability strategies using PROMETHEE and fuzzy entropy methods

Ighravwe

Oke

2017

J Build Rehabil

View full text Add to dashboard Cite

Today, maintenance plays a significant responsibility in all stages of equipment life due to strong government interests in environmentally conscious manufacturing. The need of the hour is to ignore the sparse attention to sustainable maintenance research and pursue valuable links between maintenance strategy and sustainable maintenance. In maintenance strategy choice, available reports have not sufficiently addressed the imbalance caused by uncertainties in maintenance practices. In addition, current reports on maintenance strategy sustainability focus on technical and economic aspects of maintenance and scantily treat environmental, social and safety criteria. This affects the quality of decisions in maintenance systems. To remedy this situation, this study applies fuzzy entropy weight and PROMETHEE (Preference Ranking Organisation Method for Enrichment Evaluation) in ranking maintenance sustainability strategies. The proposed approach is tested in a cement plant. Based on the choice criteria, the PROMETHEE methods results identified the best maintenance strategy as maintenance optimisation strategy. Workforce training strategy was identified as the worst maintenance sustainability strategy. These obtained results were compared with fuzzy TOPSIS (Technique of Preference Order by Similarity to Ideal Solution) approach and the practical application of the approach was verified. The results serve as a basis and a platform for further application of the approach in other manufacturing companies.

show abstract

“…Ramirez-Hernandez et al (2007) reported the translation of time from calendar-based to non-calendar-based in programmes involving the scheduling of preventive maintenance tasks. Ighravwe and Oke (2014) optimised maintenance workforce cost and productivity under full-and part-time working conditions. Sanchez et al (2009) used a multiobjective genetic algorithm (MOGA) to optimised unavailability and cost criteria in maintenance and testing of machines under uncertainty conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

A Mixed-integer Multi-objective Maintenance and Production Workforce Planning Model

Ighravwe

Oke

2017

Process Integr Optim Sustain

View full text Add to dashboard Cite

This study tackles the dilemma of producing a cooperative workforce planning involving maintenance and production departments. Its focus is on instituting workforce equilibrium between maintenance and production departments. This is necessary in order to ensure the optimal utilisation of manufacturing resources (time, equipment and funds). This maintenance-production problem was modelled using a mixed-integer multi-objective approach. The model minimises the workforce, rework and scrap, inventory holding cost and machine usage costs while maximising the average achieved machine availability. The model accounts for expected products' demand, the amount of expected defective products, workforce size, rest period and finished good inventory. Due to the nonlinear relationships among the maintenanceproduction variables, a big bang-big crunch (BB-BC) algorithm and genetic algorithm (GA) were selected as solution methods for the model. The proposed model performance was validated in a household utensils manufacturing plant under the conditions of workers' rest and without rest periods considerations. Based on the results obtained, the BB-BC algorithm performed better than the GA in terms of fitness function and computational time. The model performance with workers' rest period consideration generated higher achieved machine availability value than when workers' rest period was not considered. The optimised maintenance-production variables results confirmed the model's capability to generate acceptable solutions for the case study.

show abstract

A non-zero integer non-linear programming model for maintenance workforce sizing

Cited by 30 publications

References 28 publications

Logistical modelling of managerial decisions in social and marketing business systems

Logistical modelling of managerial decisions in social and marketing business systems

A multi-hierarchical framework for ranking maintenance sustainability strategies using PROMETHEE and fuzzy entropy methods

A Mixed-integer Multi-objective Maintenance and Production Workforce Planning Model

Contact Info

Product

Resources

About