Un algoritmo para el problema de biflujo máximo simétrico no dirigido

En este trabajo proponemos un algoritmo de O(nmlogU) para resolver el problema de biflujo máximo simétrico en una red no dirigida. Para resolver este problema se introduce un cambio de variable que permite dividir el problema original en dos problemas de flujo máximo. De esta manera se obtiene un algoritmo sencillo y eficiente donde se utilizan las herramientas computacionales propias de la resolución del clásico problema de maximizar un único flujo

SHORTEST PATH SIMPLEX ALGORITHM WITH A MULTIPLE PIVOT RULE: A COMPARATIVE STUDY

This paper introduces a new multiple pivot shortest path simplex method by choosing a subset of non-basic arcs to simultaneously enter into the basis. It is shown that the proposed shortest path simplex method requires O(n) multiple pivots and its running time is O(nm). Results from a computational study comparing the proposed method from previously known methods are reported. The experimental show that the proposed rule is more efficient than the considered shortest path simplex pivot rules.Shortest path problem, simplex shortest path algorithms, multiple pivot rule, experimental analysis

An algorithmic study of the Maximum Flow problem: A comparative statistical analysis

Network programming, Maximum Flow Algorithm, Experimental Design, Statistical Analysis, 90C27,

Preemptive benchmarking problem: An approach for official statistics in small areas

National Statistical Agencies and Autonomous Institutions are extremely interested in using information from those areas that are actually smaller than the actual areas for which a survey is initially designed. As such, small area estimation and its application are valuable when conducting research on Official Statistics. A wide range of different methods are available which provide estimations to small area levels, being reasonable to guarantee that they add up to the published design-based estimations in a large area that includes these small areas. This requirement is known as benchmarking. Different algorithms, all based on distances between original data and modified data, are introduced in this paper, with the intention of satisfying the benchmarking property. We provide rules to apply these proposed calibrated methods according to user criteria. Goal programming with priorities methodology is used to represent user preferences. The result is a collection of different interdependent network flow problems. Some of these problems require the development of ad hoc methods. The introduced methods are assessed by a Monte Carlo simulation study using the Spanish Labour Force Survey in the Canary Islands. The results also show that the consistency of the estimator is independent of the used calibrated methods, but it does depend on the benchmarking weights.Small area estimation Benchmarking property Networks flows Goal programming

A network flow-based method to solve performance cost and makespan open-shop scheduling problems with time-windows

This paper deals with several bicriteria open-shop scheduling problems where jobs are pre-emptable and their corresponding time-windows must be strictly respected. The criteria are a performance cost and the makespan. Network flow approaches are used in a lexmin procedure with a bounded makespan and the considered bicriteria problems are solved. Finally, the computational complexity of the algorithm and a numerical example are reported.90B35 90B10 90C27 Pre-emptive open-shop scheduling Bicriteria optimization Network flow approach Time-windows Max-flow parametrical algorithm

A primal–dual simplex algorithm for bi-objective network flow problems

In this paper we develop a primal–dual simplex algorithm for the bi-objective linear minimum cost network flow problem. This algorithm improves the general primal–dual simplex algorithm for multi-objective linear programs by Ehrgott et al. (J Optim Theory Appl 134:483–497, 2007). We illustrate the algorithm with an example and provide numerical results

Using multi-UAV for rescue environment mapping: task planning optimization approach

Rescuing survivors in unknown environment can be extreme difficulty. The use of UAVs to map the environment and also to obtain remote information can benefit the rescue tasks. This paper proposes an organizational system for multi-UAVs to map indoor environments that have been affected by a natural disaster. The robot’s organization is focused on avoiding possible collisions between swarm’s members, and also to prevent searching in locations that have already discovered. This organizational approach is inspired by bees behavior. Thus, the multi- UAVs must search, in a collaborative way, in order to map the scenario in the shortest possible time and, consequently, to travel the shortest reasonable distance. Therefore, three strategies were evaluated in a simulation scenario created in the V-REP software. The results indicate the feasibility of the proposed approach and compare the three plans based on the number of locations discovered and the path taken by each UAV.This work is supported by Grant #337/2014 (Fundação Araucária - Brazil), the grant from the bi-national cooperation scheme of UTFPR- IPB and by FCT – Fundação para a Ciência e Tecnologia within the Projects Scopem UIDB/05757/2020.info:eu-repo/semantics/publishedVersio

New efficient shortest path simplex algorithm: pseudo permanent labels instead of permanent labels

Shortest path problem, Shortest path simplex algorithm, Pseudo permanent labels,