A bi-objective model for scheduling of multiple projects under multi-skilled workforce for distributed load energy usage

A Systematic Investigation Into the Control of Roughness on the Flow Properties of 3D‐Printed Fractures

“…e m distributions narrow with increasing σ′, illustrated by positive skewness (Figure 6a), consistent with previously measured rough fracture aperture distributions (Gentier et al, 1997;Pruess & Tsang, 1990;Sharifzadeh et al, 2008;Tatone & Grasselli, 2012;. −Δe m with σ′ has also been shown to be heterogeneous, with skewness increasing in prevalence (i.e., longer tail) (Javanmard et al, 2021;Kang et al, 2016;Muralidharan et al, 2004;Unger & Mase, 1993;R. Walsh et al, 2008), aligning with distributions seen here, albeit subtly.…”

“…It is also the case that despite a certain correlation between R c and tortuosity, this relationship alone cannot adequately capture aperture heterogeneity (in relation to tortuosity), as R c only accounts for a portion of the fracture surface (Rong et al, 2020). Tortuosity is therefore also dependent on the evolution of overall surface and resulting aperture structure roughness, which is observed to increase ( m E e  /e m = 0.37 to 0.66) with σ′, with e m decreasing more rapidly than m E e  , consistent with previous studies (Javanmard et al, 2021). Although it is evident that tortuosity plays a significant role in FR#7_2's k f decrease, and, by proxy, the k f response of FR#1-FR#6, identifying which tortuosity-contributing parameter primarily influences k f is key.…”

“…Li et al, 2008;Yeo, 2001). k f estimation from this method (Javanmard et al, 2021) (Figure 8, dashed yellow line): (13) yields reasonable k f estimation at the highest σ′ (within 39%). Nevertheless, insufficient k f predictions given by these relations imply surface roughness should be considered to better predict experimental k f , particularly at lower σ′.…”

“…Li et al, 2008;Yeo, 2001). k f estimation from this method (Javanmard et al, 2021) (Figure 8, dashed yellow line):…”

The Multi-Skilled Resource-Constrained Project Scheduling Problem: A Systematic Review and an Exploration of Future Landscapes

“…To solve this variant, various heuristic algorithms were proposed, such as a serial greedy algorithm and a binary-tree-based search algorithm. In addition, Javanmard et al [75] and Myszkowski et al [76] proposed intelligent algorithms optimized with the Taguchi method and Evolutionary Algorithm, respectively, to address scheduling problems with multi-skilled workforces. Furthermore, Shahnazari-Shahrezaei et al [77] proposed two meta-heuristic algorithms based on Differential Evolution and Particle Swarm Optimization to solve the MS-RCPSP.…”