A Customized Hybrid Approach to Infrastructure Maintenance Scheduling in Railroad Networks under Variable Productivities

Abstract

Railroads are maintained routinely by using various types of rail‐bound machines so as to achieve the longest possible rail life and reduce the safety risks associated with unanticipated rail failures. The rail maintenance routing and scheduling problem (RMRSP), which involves routing of multiple maintenance vehicles and scheduling of hundreds of maintenance jobs over a large‐scale network, is usually subject to various types of complex constraints and extremely difficult to solve. This article proposes a vehicle routing problem with time windows (VRPTW) formulation for RMRSP and develops a customized stepwise algorithm to solve the problem. A series of numerical experiments are conducted to demonstrate that the proposed algorithm works very effectively, significantly outperforming the state‐of‐the‐art commercial solver. The results of two real‐world instances from a Class I railroad company show that the proposed model and solution algorithm enable the expensive maintenance vehicles to achieve a higher level of utilization, that is, spending more time on working and less time on deadhead traveling.

Drone scheduling for construction site surveillance

“…Model [P] is challenging to solve because it has complex nonlinear constraints () and () and cannot be solved by off‐the‐shelf solvers (Adeli & Karim, 2014; García‐Nieves, Ponz‐Tienda, Salcedo‐Bernal, & Pellicer, 2018; Jiang & Adeli, 2003; Tang, Liu, Wang, Sun, & Kandil, 2018; Wang, Yan, & Qu, 2019; Xie, Lei, & Ouyang, 2018). One approach is to apply nonlinear optimization methods (Arcaro & Adeli, 2019; Bie, Xiong, Yan, & Qu, 2020; Z. Chen & Liu, 2019; Pu et al., 2019; Qu, Yu, Zhou, Lin, & Wang, 2020; Zavadskas, Antucheviciene, Turskis, & Adeli, 2016; Zavadskas, Antucheviciene, Vilutiene, & Adeli, 2018; Zhang et al., 2019; Zhou, Yu, & Qu, 2020), such as Newton method or quasi‐Newton method (Branam, Arcaro, & Adeli, 2019), but they do not guarantee global optimality.…”

Optimal transportation planning for prefabricated products in construction

“…To bridge the gap, we employ mathematical models and optimization methods to address this transportation problem for construction. Optimization models have been successfully applied to other transportation problems such as rail network maintenance (Xie, Lei, & Ouyang, 2018), bus route design (J. Yang, Jin, Wu, & Jiang, 2017), vehicle routing (Liao, 2017), freeway cost minimization (Jiang & Adeli, 2003;Karim & Adeli, 2003), and road network design (Wang & Szeto, 2017) and construction problems such as cost estimation (Adeli & Karim, 2014;Karim & Adeli, 1999;Rafiei & Adeli, 2018;Senouci & Adeli, 2001), surveillance camera placement (X.…”

“…To bridge the gap, we employ mathematical models and optimization methods to address this transportation problem for construction. Optimization models have been successfully applied to other transportation problems such as rail network maintenance (Xie, Lei, & Ouyang, ), bus route design (J. Yang, Jin, Wu, & Jiang, ), vehicle routing (Liao, ), freeway cost minimization (Jiang & Adeli, ; Karim & Adeli, ), and road network design (Wang & Szeto, ) and construction problems such as cost estimation (Adeli & Karim, ; Karim & Adeli, ; Rafiei & Adeli, ; Senouci & Adeli, ), surveillance camera placement (X. Yang et al., ), structure analysis (Acharya, Oh, Hagiwara, Tan, & Adeli, ; Branam, Arcaro, & Adeli, ; Park, Lee, Adeli, & Lee, ), sustainability (Zavadskas, Antucheviciene, Vilutiene, & Adeli, ), and resource scheduling (García‐Nieves, Ponz‐Tienda, Salcedo‐Bernal, & Pellicer, ). Both exact and heuristic algorithms are used to solve these models.…”

Multi-objective model for optimizing railway infrastructure asset renewal

“…Other aspects were also considered in the maintenance-only case, such as e.g. repair team management (Peng et al, 2011;Ouyang, 2012, 2014), risk and other stochastic aspects, combined with operational aspects (Baldi et al, 2016;Consilvio et al, 2018;Xie et al, 2018).…”