Over the past few decades, neuroscience experiments have become increasingly complex and naturalistic. Experimental design has in turn more challenging, as must conform to an ever-increasing diversity of constraints. In this article, we demonstrate how process can be greatly assisted using optimization tool known mixed-integer linear programming (MILP). MILP provides a rich framework for incorp...

We study the performance of Empirical Revenue Maximizing (ERM) mechanism in a single-item, single-seller, single-buyer setting. assume buyer’s valuation is drawn from regular distribution F and that seller has access to two independently samples F. By solving family mixed-integer linear programs (MILPs), ERM proven guarantee at least .5914 times optimal revenue expectation. Using solutions thes...

We present an overview of noncommercial software tools for the solution of mixed-integer linear programs (MILPs). We first review solution methodologies for MILPs and then present an overview of the available software, including detailed descriptions of eight software packages available under open-source or other noncommercial licenses. Each package is categorized as a black-box solver, a calla...

In the rst part of the paper we present a framework for describing basic tech niques to improve the representation of a mixed integer programming problem We elaborate on identi cation of infeasibility and redundancy improvement of bounds and coe cients and xing of binary variables In the second part of the paper we discuss recent extensions to these basic techniques and elaborate on the investi...