Fields / Portal
Flow, Constraints, and Forecasts
Industrial engineering designs the systems people work inside. Three tools carry most of it. Little’s law ties together how much is waiting, how fast it arrives, and how long it stays. A linear program chooses the best plan under limits. A forecast checked against a baseline earns trust only by beating the naive guess. A close friend trained here; this is the field in my circle most fluent in turning complexity into measurable results.
Principles
L = λW
Average work in the system equals arrival rate times average time in it. Cut the wait and the pile shrinks; raise arrivals without capacity and it grows. Schedulers live inside this identity.
wiki: Little’s lawA linear program
Name the objective, the constraints, and the decisions, and the simplex method finds the best corner of what is allowed. See optimization.
wiki: linear programmingBeat the baseline
A forecast is only as good as its margin over the naive guess: last period, or the same period last year. See forecasting.
fpp3: simple benchmarksParallel and Competing Theories
Operations research grew up in Western militaries and factories. These systems, from India and Kenya, solved flow and payment problems the Western playbook had not planned for, and they are now studied as models in their own right.
Mumbai’s dabbawalas
About five thousand couriers deliver some two hundred thousand home-cooked lunches a day with a color-coded system and almost no errors, studied by business schools as a model of reliable flow.
wiki: dabbawalaM-Pesa
Kenya’s mobile-money system turned ordinary phones and corner agents into a payment network, a process redesign that reached people banks had not.
wiki: M-Pesa