Amir Elalouf

An improved FPTAS for mobile agent routing with time constraints

Camponogara and Shima (2010) developed an e-approximation algorithm (FPTAS) for the mobile agent routing problem in which a benefit function determines how visits to different sites contribute to the agents mission. The benefit is to be maximized under a time constraint. They reduced the problem to the constrained longest-path problem in a graph. In this note we present a modified FPTAS that improves on their result by a factor of () () log log / nh b b, where b and b are an upper bound and a lower bound on the maximum benefit, respectively, n is the number of nodes, and h is the length of the longest path (in hops) in the graph.

Efficient Routing of Mobile Agents for Agent-Based Integrated Enterprise Management: A General Acceleration Technique

Modern manufacturing enterprises are steadily moving towards open architectures wherein manufacturing activities are integrated with the activities of suppliers, customers, and partners within complex supply chains. Agent-based technology provides a natural way to design and implement such integration. We model the supply chain as a directed graph in which the vertices represent computers or individual agents and edges represent links. Thus the problem of enhancing the efficiency of mobile agents reduces to the problem of finding resource-constrained extremal paths in the graph. We study e-approximation algorithms for solving the considered problems. We suggest a general three-stage technique, which follows and extends an earlier computational scheme in the literature for the constrained path problems (CPP). The new technique essentially improves on several earlier algorithms and also provides new aproach for contructing FPTAS for the CPP.

An improved FPTAS for maximizing the weighted number of just-in-time jobs in a two-machine flow shop problem

Recently, Shabtay and Bensoussan (2012) developed an original exact pseudo-polynomial algorithm and an efficient

Optimization of blood sample collection with timing and quality constraints

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A Multi-agent Scheduling Model for Maximizing Agent Satisfaction

-approximation algorithm (FPTAS) for maximizing the weighted number of just-in-time jobs in a two-machine flow shop problem. The complexity of the FPTAS is

A multi-criterion approach to optimal vaccination planning: Method and solution

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