scholarly journals SELECTION OF A DECISION MODEL FOR ROLLING STOCK MAINTENANCE SCHEDULING

2015 ◽  
Vol 26 (1) ◽  
pp. 135 ◽  
Author(s):  
Olabanji O Asekun ◽  
Cornelius Jacobus Fourie
Keyword(s):  
Decision Model ◽  
Maintenance Scheduling ◽  
Rolling Stock ◽  
Selection Of

scholarly journals Study of Model for Selection of Priorities for Development of Cargo Transportation

2019 ◽  
Vol 67 ◽  
pp. 02003
Author(s):  
Valerii Kuleshov ◽  
Ganna Shapoval ◽  
Maksym Kutsenko
Keyword(s):  
Regulatory Framework ◽  
Market Development ◽  
Rolling Stock ◽  
Cargo Transportation ◽  
Selection Of

The transport market of operator companies of various forms of ownership in Ukraine is constantly evolving, but the tasks associated with the selection and implementation of the priorities of the development of the transport market, the provision of railway services by the carriers - owners of rolling stock, are not fully resolved. There is no regulatory framework that determines the procedure for choosing the priorities of transport market development, their status is not defined, the relation of the selected priorities with the budget of Ukraine is not defined. Therefore, the task of improving the mechanism for selecting scientific and technological priorities for the development of these processes is relevant.

Preventive maintenance scheduling using analysis of variance-based ant lion optimizer

2018 ◽  
Vol 15 (2) ◽  
pp. 254-272 ◽  
Author(s):  
Umamaheswari Elango ◽  
Ganesan Sivarajan ◽  
Abirami Manoharan ◽  
Subramanian Srikrishna
Keyword(s):  
Analysis Of Variance ◽  
Heuristic Algorithm ◽  
Heuristic Algorithms ◽  
Statistical Tests ◽  
Population Based ◽  
Maintenance Scheduling ◽  
Content Type ◽  
Ant Lion Optimizer ◽  
Ant Lion ◽  
Selection Of

Purpose Generator maintenance scheduling (GMS) is an essential task for electric power utilities as the periodical maintenance activity enhances the lifetime and also ensures the reliable and continuous operation of generating units. Though numerous meta-heuristic algorithms have been reported for the GMS solution, enhancing the existing techniques or developing new optimization procedure is still an interesting research task. The meta-heuristic algorithms are population based and the selection of their algorithmic parameters influences the quality of the solution. This paper aims to propose statistical tests guided meta-heuristic algorithm for solving the GMS problems. Design/methodology/approach The intricacy characteristics of the GMS problem in power systems necessitate an efficient and robust optimization tool. Though several meta-heuristic algorithms have been applied to solve the chosen power system operational problem, tuning of their control parameters is a protracting process. To prevail over the previously mentioned drawback, the modern meta-heuristic algorithm, namely, ant lion optimizer (ALO), is chosen as the optimization tool for solving the GMS problem. Findings The meta-heuristic algorithms are population based and require proper selection of algorithmic parameters. In this work, the ANOVA (analysis of variance) tool is proposed for selecting the most feasible decisive parameters in algorithm domain, and the statistical tests-based validation of solution quality is described. The parametric and non-parametric statistical tests are also performed to validate the selection of ALO against the various competing algorithms. The numerical and statistical results confirm that ALO is a promising tool for solving the GMS problems. Originality/value As a first attempt, ALO is applied to solve the GMS problem. Moreover, the ANOVA-based parameter selection is proposed and the statistical tests such as Wilcoxon signed rank and one-way ANOVA are conducted to validate the applicability of the intended optimization tool. The contribution of the paper can be summarized in two folds: the ANOVA-based ALO for GMS applications and statistical tests-based performance evaluation of intended algorithm.

Selection of funding schemes by a borrowing decision model: a Hong Kong case study

2006 ◽  
Vol 24 (4) ◽  
pp. 349-365 ◽  
Author(s):  
C. M. Tang ◽  
C. W. Y. Wong ◽  
A. Y. T. Leung ◽  
K. C. Lam
Keyword(s):  
Hong Kong ◽  
Decision Model ◽  
Selection Of

Strengthening method of wheelset tires

2021 ◽  
pp. 51-54
Author(s):  
D.V. Glazunov ◽  
V.N. Krotov ◽  
E.Yu. Cherkesov
Keyword(s):  
Wear Resistance ◽  
Physical Properties ◽  
Rolling Stock ◽  
Performance Tests ◽  
Limited Temperature ◽  
Main Disadvantage ◽  
Limited Temperature Range ◽  
Component Content ◽  
Selection Of ◽  
Strengthening Method

The main ways to strengthen and increase the resourse of wheelset bandage as result of which it is determined that the most economical and quick-to-implement method is the use of tribotechnical materials are considered. The main disadvantage in using of tribotechnical materials is the limited temperature range of rolling stock operation is determined. Qualitative selection of anti-wear and heat-resistant additives, as well as binder is perfomed based on the physical properties required for tribotechnical materials and the range of component content in the lubricant is determined. The wear resistance of wheelset bands is increased by 28 % as result of performance tests.

Decision model for selection of technologies to reduce IT operations energy cost in a medium-sized firm

2013 ◽  
Vol 6 (2) ◽  
pp. 151-170 ◽  
Author(s):  
Tugrul U. Daim ◽  
Ibrahim Iskin ◽  
Robert DeLay ◽  
Lokesh Honnappa ◽  
Vorakarn Chiamsiri ◽  
...  
Keyword(s):  
Energy Cost ◽  
Decision Model ◽  
It Operations ◽  
Selection Of
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