Models of maximum flows in airspace sectors in the presence of multiple constraints

Among the most interesting problems in competitive programming involve maximum flows. However, efficient algorithms for solving these problems are often difficult for students to understand at an intuitive level. One reason for this difficulty may be a lack of suitable metaphors relating these algorithms to concepts that the students already understand. This paper introduces a novel maximum flow algorithm, Tidal Flow, that is designed to be intuitive to undergraduate andpre-university computer science students.

Download Full-text

A Further Generalized Kettele Algorithm with Multiple Constraints

10.21236/ada196054 ◽

1988 ◽

Author(s):

A. Charnes ◽

D. Zhang

Keyword(s):

Multiple Constraints

Download Full-text

The Effects of Multiple Constraints on the Army's New Officer Evaluation Report

10.21236/ada404930 ◽

2002 ◽

Author(s):

Charles R. Hamilton

Keyword(s):

Multiple Constraints ◽

Evaluation Report

Download Full-text

Restricted Constraints in the Problem of Maximum Attainable Flow in Minimum Cost in a Network

Journal of Network and Information Security ◽

10.21863/jnis/2015.3.2.009 ◽

2015 ◽

Vol 3 (2) ◽

Author(s):

Nazimuddin Ahmed ◽

Shobha Duttadeka

Keyword(s):

Minimum Cost ◽

Optimal Route ◽

Precedence Relation ◽

Flow Capacity ◽

Cost Distance ◽

Realistic Situation ◽

Maximum Flows

In this paper we have considered a version of restricted constraints in the problem of maximum attainable flow (capacity) in minimum cost (distance) in a network (Ahmed, Das, & Purusotham, 2012b). By restricted constraints one means that the link(s) (cities or stations or nodes) are completed (or visited) in such a way that a particular link is to be preceded (completed or visited) by another link (precedence relation need not be immediate). Here the aim is to obtained an optimal route of a more realistic situation as to scheduling a restricted constraints to a maximum flows at a minimum cost from a source to a destination. The distance (cost) and arc capacity between any two stations are given.

Download Full-text

Computer algorithms

10.1093/oso/9780198805090.003.0008 ◽

2018 ◽

Author(s):

Mark Newman

Keyword(s):

Data Structures ◽

Analysis Of Algorithms ◽

Shortest Paths ◽

Minimum Cut ◽

Network Data ◽

Computer Algorithms ◽

Breadth First Search ◽

Augmenting Path ◽

Basic Concepts ◽

Maximum Flows

This chapter introduces some of the fundamental concepts of numerical network calculations. The chapter starts with a discussion of basic concepts of computational complexity and data structures for storing network data, then progresses to the description and analysis of algorithms for a range of network calculations: breadth-first search and its use for calculating shortest paths, shortest distances, components, closeness, and betweenness; Dijkstra's algorithm for shortest paths and distances on weighted networks; and the augmenting path algorithm for calculating maximum flows, minimum cut sets, and independent paths in networks.

Download Full-text