In computer science, program optimization, code optimization, or software optimization is the process of modifying a software system to make some aspect...

compiler will then try to optimize the result. Whole program optimization (WPO) is the compiler optimization of a program using information about all...

generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from...

equivalent code optimized for some aspect. Optimization is limited by a number of factors. Theoretical analysis indicates that some optimization problems are...

In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints are not linear equalities...

profile-directed feedback (PDF) or feedback-directed optimization (FDO), is the compiler optimization technique of using prior analyses of software artifacts...

Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets (or, equivalently...

under Craig Chambers on compilers and whole-program optimization techniques for object-oriented programming languages. He was elected to the National Academy...

An integer programming problem is a mathematical optimization or feasibility program in which some or all of the variables are restricted to be integers...

liveness. Program analysis focuses on two major areas: program optimization and program correctness. The first focuses on improving the program’s performance...

stationary points of functions. Optimization, optimisation, or optimality may also refer to: Engineering optimization Feedback-directed optimisation,...

Semidefinite programming (SDP) is a subfield of mathematical programming concerned with the optimization of a linear objective function (a user-specified...

single-objective optimization cases are presented. In the second part, test functions with their respective Pareto fronts for multi-objective optimization problems...

each cut based on programmed feed rates, reducing cycling time. The optimization is said to reduce the amount of scrapped parts, broken tools, and cutter...

Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute...

Discrete optimization is a branch of optimization in applied mathematics and computer science. As opposed to continuous optimization, some or all of the...

than the one without it. This technique of loop optimization was observed across several programming languages and compilers or interpreters. In some...

Optimization Programming Language (OPL) is an algebraic modeling language for mathematical optimization models, which makes the coding easier and shorter...

Bayesian optimization is a sequential design strategy for global optimization of black-box functions, that does not assume any functional forms. It is...

"computer programming." To avoid confusion, some practitioners prefer the term "optimization" — e.g., "quadratic optimization." The quadratic programming problem...

In the optimization literature this relationship is called the Bellman equation. In terms of mathematical optimization, dynamic programming usually refers...

would alter the program's behavior, the most common being the return value optimization (see below). Another widely implemented optimization, described in...

Linear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical...

In computing, data-oriented design is a program optimization approach motivated by efficient usage of the CPU cache, often used in video game development...

allows an optimizing compiler to perform interprocedural optimization without requiring link-time optimization, therefore allowing optimizations such as...

In mathematical optimization theory, duality or the duality principle is the principle that optimization problems may be viewed from either of two perspectives...

serves to aid program optimization, and more specifically, performance engineering. Profiling is achieved by instrumenting either the program source code...

mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic program is an optimization...

by using another overlaying optimizer, a concept known as meta-optimization, or even fine-tuned during the optimization, e.g., by means of fuzzy logic...

Gurobi Optimizer is a prescriptive analytics platform and a decision-making technology developed by Gurobi Optimization, LLC. The Gurobi Optimizer (often...