An implementation of linear interior point simplex algorithm using MATLAB

The interior point algorithm to be implemented is presented in the attached [login to view URL]" from Faigle et al. (2002). You do not need to obtain an extreme point optimal solution after the interior point algorithm terminates. 111 benchmark instances are provided in the MAT-file format. Each benchmark instance includes the following information: 1. A string 'ProbName' which includes the name of the problem instance to be solved. 2. An m? x n constraint matrix where m is the number of constraints and n is the number of variables. Note that A is represented sparsely, i.e., only the non-zero elements of A are specified in the data file. 3. An mx1 vector b of the right hand side coefficients. 4. An n x 1 vector c of the objective function coefficients. 5. An n x 1 vector LB of the lower bounds on the variables. 6. An n x 1 vector UB of the upper bounds on the variables. ## Deliverables 1) Complete and fully-functional working program(s) in executable form as well as complete source code of all work done. 2) Deliverables must be in ready-to-run condition, as follows? (depending on the nature? of the deliverables): a)? For web sites or? other server-side deliverables intended to only ever exist in one place in the Buyer's environment--Deliverables must be installed by the Seller in ready-to-run condition in the Buyer's environment. b) For all others including desktop software or software the buyer intends to distribute: A software? installation package that will install the software in ready-to-run condition on the platform(s) specified in this bid request. 3) All deliverables will be considered "work made for hire" under U.S. Copyright law. Buyer will receive exclusive and complete copyrights to all work purchased. (No GPL, GNU, 3rd party components, etc. unless all copyright ramifications are explained AND AGREED TO by the buyer on the site per the coder's Seller Legal Agreement). ## Platform WinXp