Miguel Á. Salido

3.6k total citations
85 papers, 2.4k citations indexed

About

Miguel Á. Salido is a scholar working on Industrial and Manufacturing Engineering, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Miguel Á. Salido has authored 85 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Industrial and Manufacturing Engineering, 34 papers in Computer Networks and Communications and 18 papers in Signal Processing. Recurrent topics in Miguel Á. Salido's work include Constraint Satisfaction and Optimization (33 papers), Scheduling and Optimization Algorithms (28 papers) and Advanced Manufacturing and Logistics Optimization (18 papers). Miguel Á. Salido is often cited by papers focused on Constraint Satisfaction and Optimization (33 papers), Scheduling and Optimization Algorithms (28 papers) and Advanced Manufacturing and Logistics Optimization (18 papers). Miguel Á. Salido collaborates with scholars based in Spain, China and Ireland. Miguel Á. Salido's co-authors include Adriana Giret, Federico Barber, Dunbing Tang, Min Dai, L. Ingolotti, Weidong Li, Min Dai, Amir Shabani, Behrouz Asgarian and Saeed Asil Gharebaghi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Expert Systems with Applications.

In The Last Decade

Miguel Á. Salido

81 papers receiving 2.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Miguel Á. Salido Spain	24	1.8k	346	308	269	224	85	2.4k
Yaping Ren China	28	1.9k 1.1×	190 0.5×	85 0.3×	238 0.9×	136 0.6×	73	2.5k
Chaoyong Zhang China	41	3.6k 2.0×	533 1.5×	78 0.3×	450 1.7×	264 1.2×	155	4.5k
Xiwang Guo China	28	2.1k 1.2×	318 0.9×	93 0.3×	405 1.5×	223 1.0×	173	3.2k
Leilei Meng China	31	2.5k 1.4×	263 0.8×	74 0.2×	113 0.4×	239 1.1×	110	2.9k
Jiyin Liu United Kingdom	34	3.8k 2.2×	602 1.7×	196 0.6×	216 0.8×	335 1.5×	104	4.8k
Jakob Puchinger France	22	1.5k 0.9×	337 1.0×	658 2.1×	40 0.1×	216 1.0×	57	3.0k
Alexander Fay Germany	26	2.1k 1.2×	537 1.6×	46 0.1×	193 0.7×	221 1.0×	402	3.3k
José A. Ventura United States	27	1.1k 0.6×	101 0.3×	95 0.3×	92 0.3×	251 1.1×	138	2.2k
Zhiguang Cao Singapore	29	1.2k 0.7×	607 1.8×	388 1.3×	73 0.3×	502 2.2×	93	3.1k
Zizhen Zhang China	22	714 0.4×	346 1.0×	116 0.4×	86 0.3×	85 0.4×	63	1.3k

Countries citing papers authored by Miguel Á. Salido

Since Specialization

Citations

This map shows the geographic impact of Miguel Á. Salido'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 Miguel Á. Salido with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miguel Á. Salido more than expected).

Fields of papers citing papers by Miguel Á. Salido

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miguel Á. Salido. 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 Miguel Á. Salido. The network helps show where Miguel Á. Salido may publish in the future.

Co-authorship network of co-authors of Miguel Á. Salido

This figure shows the co-authorship network connecting the top 25 collaborators of Miguel Á. Salido. A scholar is included among the top collaborators of Miguel Á. Salido 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 Miguel Á. Salido. Miguel Á. Salido is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Pérez, Christian, et al.. (2023). A Q-Learning Proposal for Tuning Genetic Algorithms in Flexible Job Shop Scheduling Problems. SHILAP Revista de lepidopterología. 36. 1 indexed citations

Shabani, Amir, et al.. (2019). Search and Rescue Optimization Algorithm for Size Optimization of Truss Structures with Discrete Variables. SHILAP Revista de lepidopterología. 3(3). 28–39. 6 indexed citations

Tang, Dunbing, et al.. (2018). An Optimization Method for Coordinating Supplier Selection and Low-Carbon Design of Product Family. International Journal of Precision Engineering and Manufacturing. 19(11). 1715–1726. 14 indexed citations

Barber, Federico, et al.. (2017). A new model and metaheuristic approach for the energy-based resource-constrained scheduling problem. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 233(1). 293–305. 9 indexed citations

Tonelli, Flavio, A. Bruzzone, Massimo Paolucci, et al.. (2016). Assessment of mathematical programming and agent-based modelling for off-line scheduling: Application to energy aware manufacturing. CIRP Annals. 65(1). 405–408. 19 indexed citations

Salido, Miguel Á., et al.. (2016). A metaheuristic technique for energy-efficiency in job-shop scheduling. The Knowledge Engineering Review. 31(5). 475–485. 25 indexed citations

Barber, Federico, et al.. (2014). PSPLIB-ENERGY: a extension of PSPLIB library to assess the energy optimization in the RCPSP. INTELIGENCIA ARTIFICIAL. 17(54). 48–48. 1 indexed citations

Wallace, Richard J., et al.. (2013). Finding robust solutions for constraint satisfaction problems with discrete and ordered domains by coverings. Artificial Intelligence Review. 44(2). 131–156. 1 indexed citations

Salido, Miguel Á., et al.. (2012). AN EXPERIENCE IN COMPUTER SCIENCE IN THE TECHNICAL INDUSTRIAL ENGINEERING ABOUT CONTINUOUS FORMATIVE EVALUATION BASED ON PROJECT-BASED LEARNING. 5198–5205.

10.

Salido, Miguel Á., et al.. (2011). Reformulating Dynamic Linear Constraint Satisfaction Problems as Weighted CSPs for Searching Robust Solutions. 1 indexed citations

11.

Salido, Miguel Á., et al.. (2010). Domain-dependent planning heuristics for locating containers in maritime terminals. 742–751. 4 indexed citations

12.

Salido, Miguel Á., et al.. (2010). Robust solutions in changing constraint satisfaction problems. 752–761. 1 indexed citations

13.

Salido, Miguel Á., Manuel Lorca, & Adriana Giret. (2010). A holonic simulation environment for smart transportation systems. International Journal of Production Research. 49(5). 1425–1439. 5 indexed citations

14.

Salido, Miguel Á., et al.. (2009). 2-C3: From Arc-Consistency to 2-Consistency.

15.

Salido, Miguel Á., et al.. (2009). An artificial intelligence planning tool for the container stacking problem. 1–4. 6 indexed citations

16.

Salido, Miguel Á., et al.. (2007). Aplicación de Metodologías Activas en la Enseñanza de Informática en la Licenciatura en Matemáticas. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje. 2. 73–78. 2 indexed citations

17.

Salido, Miguel Á., et al.. (2007). Application of Meta-Tree-Based Distributed Search to the Railway Scheduling Problem∗. 2 indexed citations

18.

Abril, M., Miguel Á. Salido, Federico Barber, et al.. (2005). A Heuristic Technique for the Capacity Assessment of Periodic Trains. 339–346. 6 indexed citations

19.

Barber, Federico, et al.. (2004). An Interactive Train Scheduling Tool for Solving and Plotting Running Maps. 1 indexed citations

20.

Barber, Federico & Miguel Á. Salido. (2003). Introducción a la programación de restricciones. 7(20). 13–30. 2 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.

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