NEOS server 4.0 administrative guide.

Abstract

The NEOS Server 4.0 provides a general Internet-based client/server as a link between users and software applications. The administrative guide covers the fundamental principals behind the operation of the NEOS Server, installation and trouble-shooting of the Server software, and implementation details of potential interest to a NEOS Server administrator. The guide also discusses making new software applications available through the Server, including areas of concern to remote solver administrators such a s m a i n taining security, providing usage instructions, and enforcing reasonable restrictions on jobs. The administrative guide is intended both as an introduction to the NEOS Server and as a reference for use when running the Server.

Exact cost minimization of a series-parallel reliable system with multiple component choices using an algebraic method

“…This encoding has allowed us to launch our data sets in the Neos Server ( [11,14,13]) under these solvers. We have chosen the 30 instances for systems with n = 8, k = 4 from Table 3, because it contains a good assortment of cases.…”

Unit Commitment in Electric Energy Systems

“…The Introduction to Optimization of the NEOS Guide provides information about the different classes of mathematical optimization problems and the software available to solve them. Most of the state-of-the-art solvers, whether commercial or open source, can be accessed for free on the NEOS Server [Czyzyk et al, 1998, Dolan, 2001, Gropp and Moré, 1997. All the computations made in the preparation of this book were carried out on the NEOS Solver.…”

Manpower Planning with Annualized Hours Flexibility: a Fuzzy Mathematical Programming Approach

“…The weight of the maximum relative capacity shortage is significantly larger than the sum of the weekly relative capacity shortages. The deterministic and fuzzy models described previously are modeled in the AMPL language and solved using a Gurobi solver using the NEOS server online facility provided by Wisconsin Institutes for Discovery at the University of Wisconsin in Madison for solving optimization problems; see Czyzyk et al (1998), Dolan (2001), Gropp andMor (1997), andNEOS (2016).…”