What (who) is delayed exchange - definition

ALGORITHM FOR SOLVING LINEAR PROGRAMS

Delayed Column Generation; Delayed column generation; Delayed column-generation

delayed exchange

n. an exchange of property to put off capital gain taxes, in which the funds are placed in a binding trust for up to 180 days while the seller acquires an "exchanged" (another similar) property, pursuant to IRS Code sec. 1031. It is sometimes called a "Starker" after the man who first used this method and survived an IRS lawsuit.

Delayed milestone

SYMPTOM

Delayed milestones; Growth retardation

Delayed milestone, also called developmental delays, is used to describe the condition where a child does not reach one of these stages at the expected age. However, in most cases, a wide variety of ages can be considered normal, and not a cause for medical concern.

https://en.wikipedia.org/wiki/Delayed_milestone

Delayed sleep phase disorder

CHRONIC MISMATCH BETWEEN A PERSON'S NORMAL DAILY RHYTHM, COMPARED TO OTHER PEOPLE AND SOCIETAL NORMS

Delayed Sleep Phase Syndrome; Delayed sleep phase; Delayed Circadian Rhythm Disorder; DSPD; Night owl insomnia; Delayed sleep-phase syndrome; Delayed sleep phase syndrome; Delayed sleep; Delayed sleep disorder; Social jet lag; Social jetlag; Delayed sleep-wake phase disorder; Delayed sleep–wake phase disorder; Delayed phase sleep disorder; Delayed Sleep Phase Disorder

Delayed sleep phase disorder (DSPD), more often known as delayed sleep phase syndrome and also as delayed sleep–wake phase disorder, is a delaying of a person's circadian rhythm (biological clock) compared to those of societal norms. The disorder affects the timing of biological rhythms including sleep, peak period of alertness, core body temperature, and hormonal cycles.

https://en.wikipedia.org/wiki/Delayed_sleep_phase_disorder

Wikipedia

Column generation

Column generation or delayed column generation is an efficient algorithm for solving large linear programs.

The overarching idea is that many linear programs are too large to consider all the variables explicitly. The idea is thus to start by solving the considered program with only a subset of its variables. Then iteratively, variables that have the potential to improve the objective function are added to the program. Once it is possible to demonstrate that adding new variables would no longer improve the value of the objective function, the procedure stops. The hope when applying a column generation algorithm is that only a very small fraction of the variables will be generated. This hope is supported by the fact that in the optimal solution, most variables will be non-basic and assume a value of zero, so the optimal solution can be found without them.

In many cases, this method allows to solve large linear programs that would otherwise be intractable. The classical example of a problem where it is successfully used is the cutting stock problem. One particular technique in linear programming which uses this kind of approach is the Dantzig–Wolfe decomposition algorithm. Additionally, column generation has been applied to many problems such as crew scheduling, vehicle routing, and the capacitated p-median problem.

https://en.wikipedia.org/wiki/Column generation