update readme

README.md

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 # Robustness Analysis for Adaptive Optimization
 
 [![License: MIT][license-badge]][license]
-[![DOI][Zenodo-badge]][Zenodo-url]
+<!-- [![DOI][Zenodo-badge]][Zenodo-url] -->
 
 This repository provides code for applying _Robustness_ _Analysis_ (RA). 
 RA is used to analyze the performance of a particular solution under variation in the uncertain parameters of an optimization problem.
@@ -46,7 +46,8 @@ For more information about these problems we refer to the [preprint-paper]. -->
 
 ## Illustrative Example
 
-We highlight the difference between SA, RA for static optimization and RA for adaptive optimization using the illustrative example as described in Section 2.2 of the [preprint-paper].  
+We highlight the difference between SA, RA for static optimization and RA for adaptive optimization using the illustrative example as described in Section 2.2 of the paper.
+<!-- [preprint-paper].   -->
 
 We assume to have access to a randomly generated data set of $N=1000$ realizations of $(c_{A,1}, c_{A,2})$ and use this scenario data to analyze the performance of our nominal solution in a 3-stage setting. 
 Then, using the same set of scenarios, we highlight the difference between SA, RA in a static setting and RA in an adaptive setting, by comparing the results from applying these three methods. 
@@ -85,9 +86,9 @@ Was our software useful to you? Great! You can cite us using:
 
 [license]:              		https://opensource.org/license/mit/
 [license-badge]:        		https://img.shields.io/badge/license-MIT-blue
-[Zenodo-url]:           		[INSERT LINK TO ZENODO]
+<!-- [Zenodo-url]:           		[INSERT LINK TO ZENODO]
 [Zenodo-badge]: 				https://zenodo.org/badge/494070848.svg
-[preprint-paper]:          		[INSERT LINK TO PAPER]
+[preprint-paper]:          		[INSERT LINK TO PAPER] -->
 
 
 <!-- https://doi.org/10.5281/zenodo.10143595 -->