Supply chain management: An opportunity for metaheuristics

In today’s highly competitive and global marketplace the pressure on organizations to find new ways to create and deliver value to customers grows ever stronger. In the last two decades, logistics and supply chain has moved to the center stage. There has been a growing recognition that it is through an effective management of the logistics function and the supply chain that the goal of cost reduction and service enhancement can be achieved. The key to success in Supply Chain Management (SCM) require heavy emphasis on integration of activities, cooperation, coordination and information sharing throughout the entire supply chain, from suppliers to customers. To be able to respond to the challenge of integration there is the need of sophisticated decision support systems based on powerful mathematical models and solution techniques, together with the advances in information and communication technologies. The industry and the academia have become increasingly interested in SCM to be able to respond to the problems and issues posed by the changes in the logistics and supply chain. We present a brief discussion on the important issues in SCM. We then argue that metaheuristics can play an important role in solving complex supply chain related problems derived by the importance of designing and managing the entire supply chain as a single entity. We will focus specially on the Iterated Local Search, Tabu Search and Scatter Search as the ones, but not limited to, with great potential to be used on solving the SCM related problems. We will present briefly some successful applications.Supply chain management, metaheuristics, iterated local search, tabu search and scatter search

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

EVEREST IST - 2002 - 00185 : D23 : final report

Deliverable públic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Enhancing QoS provisioning and granularity in next generation internet

Next Generation IP technology has the potential to prevail, both in the access and in the core networks, as we are moving towards a multi-service, multimedia and high-speed networking environment. Many new applications, including the multimedia applications, have been developed and deployed, and demand Quality of Service (QoS) support from the Internet, in addition to the current best effort service. Therefore, QoS provisioning techniques in the Internet to guarantee some specific QoS parameters are more a requirement than a desire. Due to the large amount of data flows and bandwidth demand, as well as the various QoS requirements, scalability and fine granularity in QoS provisioning are required. In this dissertation, the end-to-end QoS provisioning mechanisms are mainly studied, in order to provide scalable services with fine granularity to the users, so that both users and network service providers can achieve more benefits from the QoS provisioned in the network. To provide the end-to-end QoS guarantee, single-node QoS provisioning schemes have to be deployed at each router, and therefore, in this dissertation, such schemes are studied prior to the study of the end-to-end QoS provisioning mechanisms. Specifically, the effective sharing of the output bandwidth among the large amount of data flows is studied, so that fairness in the bandwidth allocation among the flows can be achieved in a scalable fashion. A dual-rate grouping architecture is proposed in this dissertation, in which the granularity in rate allocation can be enhanced, while the scalability of the one-rate grouping architecture is still maintained. It is demonstrated that the dual-rate grouping architecture approximates the ideal per-flow based PFQ architecture better than the one-rate grouping architecture, and provides better immunity capability. On the end-to-end QoS provisioning, a new Endpoint Admission Control scheme for Diffserv networks, referred to as Explicit Endpoint Admission Control (EEAC), is proposed, in which the admission control decision is made by the end hosts based on the end-to-end performance of the network. A novel concept, namely the service vector, is introduced, by which an end host can choose different services at different routers along its data path. Thus, the proposed service provisioning paradigm decouples the end-to-end QoS provisioning from the service provisioning at each router, and the end-to-end QoS granularity in the Diffserv networks can be enhanced, while the implementation complexity of the Diffserv model is maintained. Furthermore, several aspects of the implementation of the EEAC and service vector paradigm, referred to as EEAC-SV, in the Diffserv architecture are also investigated. The performance analysis and simulation results demonstrate that the proposed EEAC-SV scheme, not only increases the benefit to the service users, but also enhances the benefit to the network service provider in terms of network resource utilization. The study also indicates that the proposed EEAC-SV scheme can provide a compatible and friendly networking environment to the conventional TCP flows, and the scheme can be deployed in the current Internet in an incremental and gradual fashion