Reflections on the Evolution of Operations Management

Stephen C. Graves (2021) Reflections on the Evolution of Operations Management. Management Science 67(9):5379-5388. https://doi.org/10.1287/mnsc.2020.3802

In this paper, I provide some observations on how the academic field of operations management has changed over the past 40 years. For this purpose, I have identified and classified the operations management (OM) papers published in Management Science in 1976 and in 2016. From this review, I comment on what’s changed, what’s new, and what we might see in the future. In reflecting on these changes, I also document and discuss how the OM editorial structure and mission have evolved at Management Science over this time.

Robust and Adaptive Optimization

Dimitris Bertsimas and Dick Den Hertog, Robust and Adaptive Optimization, Dynamic Ideas, 2022.

The purpose of this book is to provide a unified, insightful, and original treatment of robust and adaptive optimization.

用大數據抓用戶胃口

林步昇譯，平台假象：拆解超級平台的神話，分析數位生態系的深層特徵，建立在數位環境中不被吞噬的結構性優勢，天下雜誌，2022

Jonathan A. Knee, The Platform Delusion: Who Wins and Who Loses in the Age of Tech Titans, Portfolio, 2021.

非讀 BOOK

Global Optimization via Optimal Decision Trees

Dimitris Bertsimas and Berk Öztürk, Global Optimization via Optimal Decision Trees, arXiv:2202.06017. (Code in Julia)

The global optimization literature places large emphasis on reducing intractable optimization problems into more tractable structured optimization forms. In order to achieve this goal, many existing methods are restricted to optimization over explicit constraints and objectives that use a subset of possible mathematical primitives. These are limiting in real-world contexts where more general explicit and black box constraints appear. Leveraging the dramatic speed improvements in mixed-integer optimization (MIO) and recent research in machine learning, we propose a new method to learn MIO-compatible approximations of global optimization problems using optimal decision trees with hyperplanes (OCT-Hs). This constraint learning approach only requires a bounded variable domain, and can address both explicit and inexplicit constraints. We solve the MIO approximation efficiently to find a near-optimal, near-feasible solution to the global optimization problem. We further improve the solution using a series of projected gradient descent iterations. We test the method on a number of numerical benchmarks from the literature as well as real-world design problems, demonstrating its promise in finding global optima efficiently.

Python for Data Analysis

Wes McKinney, Python for Data Analysis, O'Reilly, third edition, 2022. (Open access)

Wes McKinney is an open source software developer focusing on analytical computing. He created the Python pandas project and is a co-creator of Apache Arrow, his current focus. 

半導體產業人力資源危機與管理

林育中，半導體產業人力資源危機與管理(上)，DIGITIMES，2022-09-07

長期人力資源匱乏問題的解決方式，不外是企業內部作為以及政府政策2種解決方式，政策雖然效果涵蓋面較廣，但是要達到效果的時間頗長，可能緩不濟急；企業內部作為只依賴企業的意志與力量，效果較快而且對企業有針對性。...

密涅瓦的思考習慣訓練

李佳達、劉劭穎、黃禮宏，全球人才搶著學！密涅瓦的思考習慣訓練，究竟出版社，2022

密涅瓦大學決策思考力四大重點