Automation in Manufacturing and Services

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A* Algorithm

Acceptance-Rejection Method

A heuristic search procedure that selects a node in its search tree for expansion such that the selected node has minimum value of the sum of the cost to reach the node plus a heuristic cost value for that node, where the heuristic cost underestimates the true minimum cost of completion.

In stochastic or Monte Carlo simulation, a method for sampling from a given difficult target probability distribution by sampling from a distribution that is close to the target distribution and relatively easy to sample but possibly rejecting the generated output. Sometimes just called the rejection method.

See

See

▶ Artificial Intelligence

▶ Monte Carlo Methods ▶ Monte Carlo Simulation ▶ Simulation of Stochastic Discrete-Event Systems

References Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4, 100–107. Pearl, J. (1984). Heuristics. Reading, MA: Addison-Wesley.

Accounting Prices ▶ Shadow Prices

Acceptance Sampling

Accreditation

▶ Quality Control

▶ Model Accreditation

S.I. Gass, M.C. Fu (eds.), Encyclopedia of Operations Research and Management Science, DOI 10.1007/978-1-4419-1153-7, # Springer Science+Business Media New York 2013

A

2

Active Constraint

Active Constraint

Activity-Analysis Problem

A constraint in an optimization problem that is satisfied exactly by a solution.

A linear-programming problem of the form Maximize cx, subject to Ax  b, x  0. The variables xj of the vector x are quantities of products to be produced. The bi coefficients of the resource vector b represent the amount of resource i that is available for production, the cj coefficients represent the value (profit) of one unit of output xj, and the coefficients aij of the technological matrix A represent the amount of resource i required to produce one unit of product j. The aij are termed technological or input-output coefficients. The objective function cx represents some measure of value of the total production.

See ▶ Inactive Constraint ▶ Slack Variable ▶ Surplus Variable

Active Set Methods ▶ Quadratic Programming

See ▶ Input–Output Analysis ▶ Input–Output Coefficients ▶ Linear Programming

Activity (1) A structural variable whose value (level) is to be computed in a linear programming problem. (2) Project work items having specific beginning and completion points and durations.

Acyclic Network A network that contains no cycles.

See See ▶ Network Planning ▶ Project Management ▶ Structural Variables

▶ Graph Theory ▶ Network Optimization

Adjacent Activity Level The value taken by a structural variable in an intermediate or final solution to a linear programming problem.

Nodes of a graph or network are adjacent if they are joined by an edge; edges are adjacent if they share a common node.

See See ▶ Structural Variables

▶ Graph Theory ▶ Network Optimization

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Adjacent (Neighboring) Extreme Points Two extreme points of a polyhedron that are connecte