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In "Operations Research: Topics, Impact and Trends from 1952–2019," A. Calma, W. Ho, L. Shao, and H. Li retrospectively look at 68 years of publication of the Operations Research. Using 5,440 journal articles, they highlight the top contributing countries and authors and top research methods and problems investigated. Mathematical programming is the most common research method, whereas inventory is the most investigated problem. Investigations related to pricing are growing significantly. The United States, Canada, and the United Kingdom publish the most papers, with the United States and Canada having similar publication profiles per capita. Inventory is the most popular research problem studied by North American, Asian, and Middle Eastern countries, whereas European countries focus on scheduling problems. Network visualizations of the journal's last 10 years show dynamic programming as the most used method and pricing as the most studied problem. Coauthor networks on collaborations on both dynamic programming and pricing are also shown. This paper is a retrospective look at 68 years of publication output of Operations Research, revealing changes in its publications, its authors, and their impact over time and how these changes might affect researchers and practitioners in the present. A total of 5,440 journal articles from its inception in 1952 to 2019 are used. The analysis initially focuses on the most studied topics and then continues with the top research methods and research problems investigated. The top contributing countries and authors to the most investigated research problems are also studied. The results indicate that mathematical programming is the most common research method, whereas inventory is the most investigated problem. However, investigations related to pricing are growing significantly. The United States, Canada, and the United Kingdom publish the most papers, with the United States and Canada having similar publication profiles per capita. Inventory is the most popular research problem studied by North American, Asian, and Middle Eastern countries, whereas European countries focus on scheduling problems. In order to understand the latest research trend, we visualize the networks of the last 10 years of Operations Research that show dynamic programming as the most used method and pricing as the most studied problem. We further visualize the coauthor networks on both dynamic programming and pricing to identify the most significant clusters of researchers and the topics these research clusters collaborate on. Finally, we provide researchers information about where Operations Research is and where it is likely heading. [ABSTRACT FROM AUTHOR]

We study an optimal matching problem in the context of dual‐donor organ exchange, where a portion of two living donors' organs are transplanted to a single patient. This dual‐donor transplant technique is becoming more widespread for lung and liver transplants. However, multiple medical compatibility criteria pose a serious challenge for matching a patient with two compatible donors. In the United States and many other countries, laws prohibit commercial (for‐profit) deals for human organs, so donor exchanges are run by nonprofit organizations connecting donors with people in need of organs, with the goal of increasing transplant matches. We propose a simple chain mechanism in dual‐donor organ exchange to increase the number of patient–dual‐donor matches, which would maximize the number of patients receiving transplants. Based on this objective, we propose a general simple chain optimization framework for finding the maximum patient matching, taking into account multiple compatibility criteria (e.g., blood type and weight), and determine the complexity status of the problem. We provide theoretical results on the structures of simple chains, as well as a polynomial time algorithm to obtain the maximum patient matching simple chain with blood type compatibility. Through a numerical study for multiple compatibility criteria, we show that in many scenarios, a simple chain substantially increases the number of patients matched with dual donors for transplants, as opposed to exchange cycles. We also address the problem of maximizing the number of patients matched for dual‐donor organ transplants via two‐way and three‐way exchange cycles, subject to donors' and recipients' medical compatibility criteria, along with a discussion of their computational complexity. Finally, we characterize the general configurations of large n‐way exchange cycles and provide theoretical insights for their structural properties. Our findings provide general optimization models for dual‐donor organ exchange operators to increase the number of patients matched for transplant, given multiple compatibility criteria. In addition, we show how exchange operators, using simple chains, can increase patient matches and reduce simultaneous surgical resource requirements over exchange cycles. [ABSTRACT FROM AUTHOR]