Heuristics

List of Octave codes related to Chapter 27 of [1]. More...

Files
file	bestInsert.m
	Identifies the best insertion in a tour for the TSP.
file	getTourList.m
	Transforms a tour stored as a sequence of cities into a list of successors.
file	getTourSequence.m
	Transform tour stored as list of successor, into a sequence of cities.
file	insertCity.m
	Inserts a city in a tour for the TSP.
file	knapsackGreedy.m
	Solves the knapsack problem using the greedy heuristic described in section 27.1.1 of [1].
file	ksLocalSearchDeterministic.m
	Algorithm 27.3: local search for the knapsack problem.
file	ksLocalSearchRandom.m
	Implementation of a variant of the local search algorithm with random neighbors for the knapsack problen.
file	ksRandomNeighbor.m
	Algorithm 27.5: neighborhood for the knapsack problem.
file	ksSimulatedAnnealing.m
	Algorithm 27.7: simulated annealing for the knapsack problem.
file	ksVns.m
	Algorithm 27.5: VNS for the knapsack problem.
file	randomFromAtoB.m
	Compute a random integer between A and B.
file	run2702greedy.m
	Runs example 27.2 of [1], solving the problem using the greedy heuristic.
file	run2702localSearchDeterministic.m
	Runs example 27.2 of [1], solving the problem using the local search method (Table 27.6)
file	run2702localSearchRandom.m
	Runs example 27.2 of [1], solving the problem using the local search method with random neighbors.
file	run2702simAnn.m
	Runs example 27.2 of [1], solving the problem using the simulated annealing method (see Section 27.4.1 of [1]).
file	run2702vns.m
	Runs example 27.2 of [1], solving the problem using the VNS method.
file	run2703insertion.m
	Runs example 27.3 of [1], solving the problem using the greedy heuristic (Algorithm 27.2, Table 27.2, Figure 27.4)
file	run2703localSearch.m
	Runs Algorithm 27.3 on example 27.3 of [1], solving the TSP with local search (Figure 27.11, Table 27.7, Figure 27.12)
file	run2703nearestNeighrbor.m
	Runs example 27.3 of [1], solving the problem using the greedy heuristic.
file	run2703simAnn.m
	Runs example 27.3 of [1], solving the problem using simmulated annealing (Section 27.4.2 of [1] ).
file	run2703vns.m
	Runs example 27.3 of [1], solving the problem using VNS (Section 27.3.2 of [1] ).
file	subtourLength.m
	Calculate the length of a subtour of the TSP.
file	tspInsertion.m
	Algorithm 27.2: insertion heuristic for TSP.
file	tspInsertionLocalSearch.m
	Local search method for the TSP based on the insertion heuristic, as described in Section 27.3.2 of [1].
file	tspLocalSearch.m
	Algorithm 27.3: local search for the TSP.
file	tspNearestNeighbor.m
	Algorithm 27.1: nearest neighbor heuristic for TSP.
file	tspSimulatedAnnealing.m
	Algorithm 27.7: simulated annealing for the TSP.
file	tspTourLength.m
	Calculate the length of a tour of the TSP.
file	tspVns.m
	Implements the VNS to solve the TSP, as described in Section 27.3.2 of [1].
file	twoOpt.m
	Perform a 2-opt operation of a list of cities.
file	twoOptNeighborhood.m
	Generate the 2-opt neightborhood for the TSP.
file	twoOptRandomNeighbor.m
	Generate one random 2-opt neighbor for the TSP.

Detailed Description

List of Octave codes related to Chapter 27 of [1].