Thanks to the many members of the NEOS community, several third-party interfaces exist allowing users to utilize the NEOS Server in additional ways. The following is a list of these interfaces: Julia R Pyomo OpenSolver SolverStudio Javascript Client PIFOP — online AMPL IDE Julia A third-party Julia interface to the …
Given a list of activities required to complete a project along with the duration of each activity and the dependencies between activities, the objective of the Critical Path Method (CPM) is to determine the sequence of activities that minimizes the latest completion time.
This pivot tool was developed by Robert Vanderbei at Princeton University to solve network flow problems.
Hardware specialization has emerged as an important way to sustain performance improvements of microprocessors to address transistor energy efficiency challenges and general purpose processing’s inefficiencies. The insight of many specialization techniques is to “map” large regions of computation to the hardware, breaking away from instruction-by-instruction pipelined execution and instead adopting a spatial architecture paradigm. The optimization problem we solve is to schedule computation nodes (in a Directed Acyclic Graph) to the spatial architecture’s ISA-exposed hardware resources. Download GAMS Code
Generating custom instruction candidates from an application is the process of analyzing the intermediate representation of the program, and finding subgraphs which can be made into instructions. Depending on the target system, these candidates must have certain properties in terms legality (including graph structure or node types), and should improve the performance as much as possible with respect to the software execution. The optimization problem we solve is to determine the convex set of operations inside a basic block, forming a custom instruction template, which maximizes the expected latency reduction.
The Multiple Traveling Salesman Problem (mTSP) is a generalization of the Traveling Salesman Problem (TSP) in which more than one salesman is allowed. Given a set of cities, one depot where \(m\) salesmen are located, and a cost metric, the objective of the \(m\)TSP is to determine a tour for each salesman such that the total tour cost is minimized and that each city is visited exactly once by only one salesman.
The Metabolic Engineering Problem describes a new optimization approach to identify the optimal metabolic and regulatory gene deletions to maximize the production of a desired chemical. The case study includes an applet for experimentation.
This case study demonstrates how supermarkets can make use of ridesharing vehicles to augment their delivery fleet and how to develop a model that routes both the supermarkets vehicles and the ridesharing vehicles to satisfy customer demands. The problem can be modeled as a Heterogeneous Fleet Vehicle Routing Problem with Time Windows (HVRPTW).
The objective of the Bar Crawl Optimization Problem is to select a set of bars and determine an ordering of them in such a way as to maximize the total benefit minus the total distance subject to a budget constraint.
Listed below are common questions and answers about using the NEOS Server. NEOS Server and the solvers
