Agile manufacturing: A framework for research and development

Current practice in project management — an empirical study

Understanding the determinants of RFID adoption in the manufacturing industry

Metaheuristics are the most exciting development in approximate optimization techniques of the last two decades. They have had widespread successes in attacking a variety of difficult combinatorial optimization problems that arise in many practical areas. This bibliography provides a classification of a comprehensive list of 1380 references on the theory and application of metaheuristics. Metaheuristics include but are not limited to constraint logic programming; greedy random adaptive search procedures; natural evolutionary computation; neural networks; non-monotonic search strategies; space-search methods; simulated annealing; tabu search; threshold algorithms and their hybrids. References are presented in alphabetical order under a number of subheadings.

Metaheuristics: A bibliography

This paper contains a bibliography of all references central to bilevel and multilevel programming that the authors know of. It should be regarded as a dynamic and permanent contribution since all the new and appropriate references that are brought to our attention will be periodically added to this bibliography. Readers are invited to suggest such additions, as well as corrections or modifications, and to obtain a copy of the LaTeX and BibTeX files that constitute this manuscript, using the guidelines contained in this paper. To classify some of the references in this bibliography a short overview of past and current research in bilevel and multilevel programming is included. For those who are interested in but unfamiliar with the references in this area, we hope that this bibliography facilitates and encourages their research.

Bilevel and multilevel programming: A bibliography review

Cet article traite de l'utilisation d'une technique a base d'algorithme genetique (GABBA) pour la resolution de problemes de Programmation Lineaire a Double-Niveau (PLDN). GABBA est utilise pour generer le vecteur de decision du leader, et la reaction du suiveur est obtenue grâce a la resolution du programme lineaire. GABBA est different des algorithmes genetiques habituels car il n'utilise que des mutations, des alleles de nombres en base 10, et une strategie de survie adaptee au PLDN. Les resultats montrent que, bien qu'il demande plus de temps CPU, GABBA s'approche davantage de l'optimum global que la technique d'optimisation par maillage de Bard [1983] pour des problemes de complexite variable

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Genetic algorithm based approach to bi-level linear programming

Technology infrastructure, business process, and managerial issues must be addressed by IT practitioners as they adapt to the business changes associated with the diffusion of RFID technology in the supply chain.

Examining RFID applications in supply chain management

Web services computing poses significant challenges as developers determine how to leverage emerging technologies to automate individual applications based on cross-organizational, heterogeneous software components.

Web services computing: advancing software interoperability

Purpose – The literature on software project management is extended into the broader domain of large‐scale IS management by studying enterprise‐wide system upgrade projects. In particular; examines the role that the intervention of project management practices (formal project methodologies and outsourcing) play in large and/or complex IS projects, which result in good project performance.Design/methodology/approach – A survey instrument was completed by 449 information systems managers about a specific upgrade project. The primary analytical approach used was structural equation modeling (SEM).Findings – It was found that neither project complexity nor project size are good indicators of meeting a project's target date. Large projects that adopted formal project management practices were more probable to meet the project target date. Projects with a high degree of complexity which involved outsourcing and adopted formal project management practices, were more likely to meet the project target date.Practic...

The importance of management practices in IS project performance: An empirical study

A decision-support approach to large-scale R&D planning is described. A quantitative model based on three analytical tools, the interaction matrix, hierarchical cluster analysis, and the Boston Consulting Group (GCG) strategic planning matrix, is used. Results of the model are used to determine the number of R&D program areas, the technological focus of each R&D program area, and the relative allocation of resources to the R&D program areas. Traditional optimization techniques for R&D planning often generate solutions without allowing for the judgement, experience, and insight of the decision maker. The decision-support approach presented supports, rather than replaces, the judgement of the R&D planner by using a graphic display of the relative position of technology clusters, and by using an interactive and iterative approach to problem solving. An application to R&D program planning for Virginia's Center for Innovative Technology's Commercial Space program is presented. >

Richard G. Mathieu

Papers

Genetic algorithm based approach to bi-level linear programming

Examining RFID applications in supply chain management

Web services computing: advancing software interoperability

The importance of management practices in IS project performance: An empirical study

A methodology for large-scale R&D planning based on cluster analysis