DE_ex.m
|
Optimization of the Rosenbrock function via differential evolution.
|
demand.m
|
Demand subroutine for the (s,S) inventory problem.
|
demandsize.m
|
Generates the size of the demand for the (s,S) inventory problem.
|
f.m
|
Cost function for the inventory system. Uses demand.m, demandsize.m, interarrival.m, leadtime.m, and order.m.
|
GA_ex_fig.m
|
An application of a binary-encoded genetic algorithm to the
satisfiability (SAT) problem. Uses SATdata.mat and sC.c.
|
interarrival.m
|
Generates a demand interarrival time for the (s,S) inventory problem.
|
leadtime.m
|
Generates a lead time for the order in the (s,S) inventory problem.
|
opt_policy.m
|
Noisy optimization for an (s,S) inventory problem, using cross-entropy. Uses f.m.
|
order.m
|
Order subroutine for the (s,S) inventory problem.
|
SA.m
|
An example of continuous optimization using simulated annealing.
|
SAnnealing_Multi_SA.m
|
Comparison of exact and approximate sampling from the Boltzmann
distribution in the simulated annealing example.
|
SATdata.mat
|
Contains the SAT instance used in the book. Load into the workspace via "load SATdata.mat".
|
sC.c
|
Evaluates the SAT score function efficiently, given a *sparse* matrix. Must first be compiled within Matlab, using "mex sC.c".
|
SCM.m
|
CE optimization via the stochastic counterpart method.
|
SCMb.m
|
Similar to SCM.m. Estimates for mu and sigma are plotted.
|
StochApprox.m
|
Noisy optimization example using stochastic approximation.
|