Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows
2006353 citationsBeatrice M. Ombuki, Brian J. Ross et al.Applied Intelligenceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Beatrice M. Ombuki
Since
Specialization
Citations
This map shows the geographic impact of Beatrice M. Ombuki's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Beatrice M. Ombuki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beatrice M. Ombuki more than expected).
Fields of papers citing papers by Beatrice M. Ombuki
This network shows the impact of papers produced by Beatrice M. Ombuki. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Beatrice M. Ombuki. The network helps show where Beatrice M. Ombuki may publish in the future.
Co-authorship network of co-authors of Beatrice M. Ombuki
This figure shows the co-authorship network connecting the top 25 collaborators of Beatrice M. Ombuki.
A scholar is included among the top collaborators of Beatrice M. Ombuki based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Beatrice M. Ombuki. Beatrice M. Ombuki is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
13 of 13 papers shown
1.
Ombuki, Beatrice M., et al.. (2006). Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows. Applied Intelligence. 24(1). 17–30.353 indexed citations breakdown →
Ombuki, Beatrice M., Morikazu Nakamura, Osamu Muta, Beatrice M. Ombuki, & Morikazu Nakamura. (2002). A HYBRID SEARCH BASED ON GENETIC ALGORITHMS AND TABU SEARCH FOR VEHICLE ROUTING. 54–5.28 indexed citations
Ombuki, Beatrice M.. (2001). An Evolutionary Algorithm Approach to the Design of Minimum Cost Survivable Networks with Bounded Rings. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 84(6). 1545–1548.3 indexed citations
11.
Ombuki, Beatrice M., Morikazu Nakamura, & Kenji Onaga. (1998). An Evolutionary Scheduling Scheme Based on gkGA Approach to the job Shop Scheduling Problem(Special Section of Papers Selected from ITC-CSCC'97). IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 81(6). 1063–1071.5 indexed citations
Ombuki, Beatrice M., Morikazu Nakamura, & Kenji Onaga. (1997). A Hybridized GA Approach to the Job Shop Problem. ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 483–486.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.