John M. Wassick

3.2k total citations · 1 hit paper
64 papers, 2.3k citations indexed

About

John M. Wassick is a scholar working on Control and Systems Engineering, Industrial and Manufacturing Engineering and Management Information Systems. According to data from OpenAlex, John M. Wassick has authored 64 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Control and Systems Engineering, 29 papers in Industrial and Manufacturing Engineering and 12 papers in Management Information Systems. Recurrent topics in John M. Wassick's work include Process Optimization and Integration (35 papers), Advanced Control Systems Optimization (33 papers) and Scheduling and Optimization Algorithms (24 papers). John M. Wassick is often cited by papers focused on Process Optimization and Integration (35 papers), Advanced Control Systems Optimization (33 papers) and Scheduling and Optimization Algorithms (24 papers). John M. Wassick collaborates with scholars based in United States, India and Netherlands. John M. Wassick's co-authors include Ignacio E. Grossmann, Fengqi You, Lorenz T. Biegler, Anshul Agarwal, Yisu Nie, Christos T. Maravelias, Yunfei Chu, Carlos Villa, Scott J. Bury and Brian King and has published in prestigious journals such as Industrial & Engineering Chemistry Research, Chemical Engineering Science and AIChE Journal.

In The Last Decade

John M. Wassick

62 papers receiving 2.2k citations

Hit Papers

Scope for industrial applications of production schedulin... 2013 2026 2017 2021 2013 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John M. Wassick United States 26 1.3k 859 424 383 218 64 2.3k
Antonio Espuña Spain 29 1.5k 1.2× 683 0.8× 700 1.7× 497 1.3× 41 0.2× 114 2.7k
Iraj Mahdavi Iran 32 534 0.4× 1.6k 1.9× 498 1.2× 330 0.9× 81 0.4× 162 3.0k
Mehmet Şevkli Türkiye 19 367 0.3× 777 0.9× 432 1.0× 292 0.8× 111 0.5× 35 2.2k
Bahman Naderi Iran 40 543 0.4× 3.3k 3.9× 622 1.5× 537 1.4× 56 0.3× 145 4.5k
Hamed Fazlollahtabar Iran 24 261 0.2× 762 0.9× 501 1.2× 339 0.9× 76 0.3× 191 1.9k
Ali Diabat United States 29 254 0.2× 471 0.5× 1.3k 3.0× 699 1.8× 249 1.1× 47 2.8k
Samir Elhedhli Canada 24 203 0.2× 780 0.9× 667 1.6× 361 0.9× 76 0.3× 61 2.0k
Chi-Guhn Lee Canada 26 660 0.5× 468 0.5× 192 0.5× 310 0.8× 44 0.2× 87 2.2k
El‐Houssaine Aghezzaf Belgium 32 386 0.3× 1.5k 1.8× 636 1.5× 775 2.0× 39 0.2× 170 3.1k
Seyed Reza Hejazi Iran 28 238 0.2× 637 0.7× 495 1.2× 418 1.1× 71 0.3× 64 2.2k

Countries citing papers authored by John M. Wassick

Since Specialization
Citations

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

Fields of papers citing papers by John M. Wassick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. Wassick. 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 John M. Wassick. The network helps show where John M. Wassick may publish in the future.

Co-authorship network of co-authors of John M. Wassick

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

All Works

20 of 20 papers shown
1.
Grossmann, Ignacio E., et al.. (2024). Iterative MILP algorithm to find alternate solutions in linear programming models. Optimization and Engineering. 25(4). 2401–2424.
2.
Wassick, John M., et al.. (2023). Integrating information, financial, and material flows in a chemical supply chain. Computers & Chemical Engineering. 178. 108363–108363. 4 indexed citations
3.
Wassick, John M., et al.. (2022). A digital twin framework for online optimization of supply chain business processes. Computers & Chemical Engineering. 166. 107972–107972. 18 indexed citations
4.
Wassick, John M., et al.. (2021). Optimization of extended business processes in digital supply chains using mathematical programming. Computers & Chemical Engineering. 152. 107323–107323. 10 indexed citations
5.
Bury, Scott J., et al.. (2019). Novel Approaches for the Integration of Planning and Scheduling. Industrial & Engineering Chemistry Research. 58(43). 19973–19984. 8 indexed citations
6.
Lafortune, Stéphane, et al.. (2019). Incorporating automation logic in online chemical production scheduling. Computers & Chemical Engineering. 128. 201–215. 5 indexed citations
7.
Wang, Yajun, Lorenz T. Biegler, Mukund R. Patel, & John M. Wassick. (2019). Robust optimization of solid-liquid batch reactors under parameter uncertainty. Chemical Engineering Science. 212. 115170–115170. 5 indexed citations
8.
Li, Zhijie, et al.. (2018). A Hybrid Blockchain Ledger for Supply Chain Visibility. 118–125. 27 indexed citations
9.
Bassett, Matthew H., et al.. (2017). Efficient formulations for dynamic warehouse location under discrete transportation costs. Computers & Chemical Engineering. 111. 311–323. 19 indexed citations
10.
García‐Herreros, Pablo, Anshul Agarwal, John M. Wassick, & Ignacio E. Grossmann. (2016). Optimizing inventory policies in process networks under uncertainty. Computers & Chemical Engineering. 92. 256–272. 18 indexed citations
11.
Wassick, John M., et al.. (2014). Supervisor Synthesis to Satisfy Safety and Reachability Requirements in Chemical Process Control. IFAC Proceedings Volumes. 47(2). 195–200. 7 indexed citations
12.
Nie, Yisu, Lorenz T. Biegler, John M. Wassick, & Carlos Villa. (2014). Extended Discrete-Time Resource Task Network Formulation for the Reactive Scheduling of a Mixed Batch/Continuous Process. Industrial & Engineering Chemistry Research. 53(44). 17112–17123. 46 indexed citations
13.
García‐Herreros, Pablo, John M. Wassick, & Ignacio E. Grossmann. (2014). Design of Resilient Supply Chains with Risk of Facility Disruptions. Industrial & Engineering Chemistry Research. 53(44). 17240–17251. 68 indexed citations
14.
Harjunkoski, Iiro, Christos T. Maravelias, Peter Bongers, et al.. (2013). Scope for industrial applications of production scheduling models and solution methods. Computers & Chemical Engineering. 62. 161–193. 353 indexed citations breakdown →
15.
Chu, Yunfei, Fengqi You, & John M. Wassick. (2013). Hybrid method integrating agent-based modeling and heuristic tree search for scheduling of complex batch processes. Computers & Chemical Engineering. 60. 277–296. 37 indexed citations
16.
Suresh, Pradeep, et al.. (2011). Real time performance measurement for batch chemical plants. Winter Simulation Conference. 2330–2340. 3 indexed citations
17.
Bury, Scott J., et al.. (2011). Generic framework for simulating networks using rule-based queue and resource-task network. Winter Simulation Conference. 2194–2205. 3 indexed citations
18.
Suresh, Pradeep, et al.. (2011). Real time performance measurement for batch chemical plants. 2325–2335. 2 indexed citations
19.
Wassick, John M., et al.. (2007). Chemical supply chain network optimization. Computers & Chemical Engineering. 32(11). 2481–2504. 37 indexed citations
20.
Wassick, John M., et al.. (1988). Internal Model Control of an Industrial Extruder. 2347–2352. 8 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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