Jay D. Schwartz

452 total citations
12 papers, 318 citations indexed

About

Jay D. Schwartz is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering and Management Science and Operations Research. According to data from OpenAlex, Jay D. Schwartz has authored 12 papers receiving a total of 318 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Control and Systems Engineering, 8 papers in Industrial and Manufacturing Engineering and 4 papers in Management Science and Operations Research. Recurrent topics in Jay D. Schwartz's work include Advanced Control Systems Optimization (8 papers), Scheduling and Optimization Algorithms (5 papers) and Flexible and Reconfigurable Manufacturing Systems (4 papers). Jay D. Schwartz is often cited by papers focused on Advanced Control Systems Optimization (8 papers), Scheduling and Optimization Algorithms (5 papers) and Flexible and Reconfigurable Manufacturing Systems (4 papers). Jay D. Schwartz collaborates with scholars based in United States and Spain. Jay D. Schwartz's co-authors include Daniel E. Rivera, Min S. Wang, Anna Razatos, Manuel R. Arahal and Karl G. Kempf and has published in prestigious journals such as Langmuir, Automatica and International Journal of Production Economics.

In The Last Decade

Jay D. Schwartz

12 papers receiving 303 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jay D. Schwartz United States	7	92	92	71	41	40	12	318
Yao‐Huei Huang Taiwan	11	24 0.3×	23 0.3×	71 1.0×	42 1.0×	17 0.4×	27	342
Mohamed Ahmed Kuwait	11	43 0.5×	46 0.5×	62 0.9×	59 1.4×	2 0.1×	22	396
Yu-Siang Lin Taiwan	11	152 1.7×	83 0.9×	80 1.1×	22 0.5×	2 0.1×	18	325
Shyamali Ghosh India	10	25 0.3×	189 2.1×	36 0.5×	155 3.8×	3 0.1×	12	381
Duy Anh Nguyễn Vietnam	11	15 0.2×	16 0.2×	30 0.4×	13 0.3×	4 0.1×	47	343
Sung Hoon Hong South Korea	11	65 0.7×	10 0.1×	96 1.4×	83 2.0×	7 0.2×	40	400
Shailendra Singh Sweden	9	44 0.5×	36 0.4×	79 1.1×	10 0.2×	3 0.1×	18	416
Marcel Müller Germany	10	96 1.0×	41 0.4×	185 2.6×	38 0.9×	1 0.0×	24	400
Z. Ouyang China	10	9 0.1×	67 0.7×	30 0.4×	25 0.6×	8 0.2×	20	679

Countries citing papers authored by Jay D. Schwartz

Since Specialization

Citations

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

Fields of papers citing papers by Jay D. Schwartz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay D. Schwartz. 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 Jay D. Schwartz. The network helps show where Jay D. Schwartz may publish in the future.

Co-authorship network of co-authors of Jay D. Schwartz

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

All Works

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12 of 12 papers shown

Schwartz, Jay D. & Daniel E. Rivera. (2014). A control-relevant approach to demand modeling for supply chain management. Computers & Chemical Engineering. 70. 78–90. 2 indexed citations

Schwartz, Jay D. & Daniel E. Rivera. (2010). A process control approach to tactical inventory management in production-inventory systems. International Journal of Production Economics. 125(1). 111–124. 58 indexed citations

Schwartz, Jay D. & Daniel E. Rivera. (2009). Control-relevant estimation of demand models for closed-loop control of a production-inventory system. 416–421. 1 indexed citations

Schwartz, Jay D., et al.. (2009). Control-Relevant Demand Forecasting for Tactical Decision-Making in Semiconductor Manufacturing Supply Chain Management. IEEE Transactions on Semiconductor Manufacturing. 22(1). 154–163. 9 indexed citations

Schwartz, Jay D. & Daniel E. Rivera. (2009). A System Identification Approach to PDE Modeling of a Semiconductor Manufacturing Process. IFAC Proceedings Volumes. 42(10). 964–969. 1 indexed citations

Schwartz, Jay D., Manuel R. Arahal, & Daniel E. Rivera. (2008). Control-relevant demand forecasting for management of a production-inventory system. 4053–4058. 1 indexed citations

Schwartz, Jay D. & Daniel E. Rivera. (2006). Simulation-based optimal tuning of model predictive control policies for supply chain management using simultaneous perturbation stochastic approximation. 27. 6 pp.–6 pp.. 7 indexed citations

Schwartz, Jay D. & Daniel E. Rivera. (2006). CONTROL-RELEVANT DEMAND MODELING FOR SUPPLY CHAIN MANAGEMENT. IFAC Proceedings Volumes. 39(1). 267–272. 7 indexed citations

Schwartz, Jay D., et al.. (2006). Simulation-based optimization of process control policies for inventory management in supply chains. Automatica. 42(8). 1311–1320. 115 indexed citations

10.

Schwartz, Jay D.. (2005). The Balanced Scorecard versus Total Quality Management: Which Is Better for Your Organization?. Military Medicine. 170(10). 855–858. 9 indexed citations

11.

Schwartz, Jay D., Daniel E. Rivera, & Karl G. Kempf. (2005). Towards control-relevant forecasting in supply chain management. 27. 202–207. 3 indexed citations

12.

Wang, Min S., et al.. (2004). Evaluating Protein Attraction and Adhesion to Biomaterials with the Atomic Force Microscope. Langmuir. 20(18). 7753–7759. 105 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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