Combining Genetic Algorithm with Constructive and Refinement Heuristics for Solving the Capacitated Vehicle Routing Problem

Lima, Stanley Jefferson de Araujo; Santos, Renato Alessandro Rocha; Araújo, Sidnei Alves de; Schimit, Pedro H. T.

doi:10.1007/978-3-319-51133-7_14

Cited by 2 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The efficiency of Simulated Annealing (SA) in solving complex combinatorial problems making it interesting for extension to multi-objective optimization [10]. In addition, it is worth noting that more and more researchers now work on hybrid methods by combining different optimization strategies [3,5,7,8].…”

Section: Introductionmentioning

confidence: 99%

Interactive Design Optimization of Layout Problems

Song

Poirson

Ravaut

et al. 2021

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

View full text Add to dashboard Cite

Layout optimization plays an important role in the field of industrial engineering. The layout problem presented here involves the real and virtual rectangular components. The real components can be the devices or buildings depending on the application. The space of accessibility associated with the real component is virtual, which allows the user to access the real component in reality, such as facility maintenance. However, most of the layout problems are NP hard. The great complexity of layout problems increase the difficulty in finding a feasible layout design in a reasonable time. To resolve these problems, we propose a hybrid constructive placing strategy which makes the search of feasible designs easier. The multi-objective application presented in this study demonstrates the effectiveness and portability of the method. Since the number of optimal layout designs can be very large, a cluster approach is followed to group all similar solutions. First, the notion of pairwise similarity indicator is introduced to analyze the similarity among the optimized layout designs. Second, the visualization of the hierarchical clustering of similarity matrix is customized. Then for each design, the user can interact with it by locally modifying the position or rotation of the component. The interactivity helps the user evaluate performance of the designs and preferable results are typically achieved.

show abstract