We must know, we will know !
万物并作，吾以观复

It previous blog, we know how to do a typical iteration in Simplex algorithm, but we will got trouble when the degeneracy happens, which will turn out that cycling can occur in our Simplex. In this blog, we will show some ways to avoid cycling in Simplex, but please note that these ways cannot make Simplex to be polynomial algorithm.

From this blog, we will talk about “rounding data” strategy and dynamic programing applied in approximation algorithm in detail. And this blog will focus on the problem “scheduling jobs on identical parallel macines”.

This blog is talking about the naïve implementation of simplex method and then focus on how to speed up simplex method. And the second idea induce the Simplex Tableau implementation.

This blog is still talking about greedy algorithm and local search. And this blog will focus on the minimum-degree Spanning Tree problem.

This blog is still talking about greedy algorithm and local search. And this blog will focus on the problem “Scheduling jobs on identical parallel machines”.

This blog is talking about how along we can move along basic feasible direction, i.e. ${ \theta }$ and talking abou the termination of Simplex Method.

This blog is still talking about gready algorithm and local search. And this blog will focus on the k-center problem.

From this blog, we will talk about gready algorithm and local search in detail. And this blog will focus on the problem “scheduling jobs with deadlines on a single machine”.