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The following is the skeleton of a generic branch and bound algorithm for minimizing an arbitrary objective function f. [3] To obtain an actual algorithm from this, one requires a bounding function bound, that computes lower bounds of f on nodes of the search tree, as well as a problem-specific branching rule.
The NIST Dictionary of Algorithms and Data Structures [1] is a reference work maintained by the U.S. National Institute of Standards and Technology. It defines a large number of terms relating to algorithms and data structures. For algorithms and data structures not necessarily mentioned here, see list of algorithms and list of data structures.
The algorithm's given problem can be a “family of problems”. [10] There are two main types of these skeletons, ‘divide and conquer’ or ‘brand and bound’. ‘Divide and conquer’ uses a map skeleton as its basis, combining this with a while skeleton to solve the problem. In map algorithms, functions on data are applied simultaneously.
Branch and price is a branch and bound method in which at each node of the search tree, columns may be added to the linear programming relaxation (LP relaxation). At the start of the algorithm, sets of columns are excluded from the LP relaxation in order to reduce the computational and memory requirements and then columns are added back to the LP relaxation as needed.
On the exact search algorithms Mallba provides branch-and-bound and dynamic-optimization skeletons. For local search heuristics Mallba supports: hill climbing , metropolis, simulated annealing , and tabu search ; and also population based heuristics derived from evolutionary algorithms such as genetic algorithms , evolution strategy, and others ...
A branch, cut and price algorithm is similar to a branch and bound algorithm but additionally includes cutting-plane methods and pricing algorithms. The user of the library can customize the algorithm in any number of ways by supplying application-specific subroutines for reading in custom data files, generating application-specific cutting ...
Various branch-and-bound algorithms, which can be used to process TSPs containing thousands of cities. Solution of a TSP with 7 cities using a simple Branch and bound algorithm. Note: The number of permutations is much less than Brute force search. Progressive improvement algorithms, which use techniques reminiscent of linear programming. This ...
Applying these two concepts results in an efficient data structure and algorithms for the representation of sets and relations. [10] [11] By extending the sharing to several BDDs, i.e. one sub-graph is used by several BDDs, the data structure Shared Reduced Ordered Binary Decision Diagram is defined. [2]