3 December 2007

Call for papers: Application of Metaheuristics in the Optimisation and Performance Measurement of Operations, Logistics and Supply Chains

Call for papers: Application of Metaheuristics in the Optimisation and Performance Measurement of Operations, Logistics and Supply Chains

A special issue of International Journal of Business Performance Management

Over the last few years, real-world optimisation problems have become increasingly complex, forcing the development of solution procedures whose efficiency is measured by their ability to find acceptable solutions within a reasonable amount of computer time. Metaheuristic optimisation stands out as a promising approach to deal with this difficult class of problems. Evolutionary algorithms have become one of the most prominent class of metaheuristics for tackling optimisation problems. However, other methodologies, such as scatter search, tabu search, ant colonies, simulated annealing and GRASP are gaining momentum. Application of metaheuristics in optimisation and performance measurement of operations, logistics and supply chain management leads to the competitive advantage and cost savings to industry and society.

Various firms have recently realised the potential of SCM in day-to-day operations management. However, they often lack the insight for the development of effective optimised performance measures which are needed to achieve a fully integrated SCM, due to lack of a balanced approach and lack of clear distinction between metrics at strategic, tactical, and operational levels. Therefore, this Special Issue aims to provide academic and practitioners with a collection of innovative research and development in optimisation and performance measurement models of operations, logistics and supply chain management.

Contributors are encouraged to submit original manuscripts that are conceptual, case studies, or empirically-based; and focus on the following or other areas related to Operations, Logistics and Supply chain, but are not limited to:
  • Performance measurement using BSC and DEA
  • Productivity, efficiency and performance benchmarking using nonparmetric OR approaches (e.g. data envelopement analysis)
  • Productivity, efficiency and performance benchmarking using statistical approaches (e.g. stochastic frontier analysis)
  • Supply chain network modelling
  • Performance measurement using metaheuristics
  • Inventory control in supply chain management
  • Reverse supply chain
  • Artificial intelligence techniques in logistics and supply chain management
  • Risk evaluation in supply chains
  • General optimisation models and methodologies for operations, logistics and supply chain management
  • Risk mitigation strategies in supply chains
  • Operations planning, scheduling and control
  • Performance measurement and productivity
  • Environmental issues in operations
  • Performance benchmarking
  • Multiobjective optimisation in logistics and supply chains
  • Operations and business process management
  • Closed-loop supply chains
  • Global operations management
  • Inventory management and coordination
  • Logistics service performance
  • Fuzzy logic and neural networks in supply chain
  • Game theory and goal programming in supply chain
Important Dates
Manuscript submission: 30 April 2008
Notification of initial decision: 30 June 2008
Notification of final acceptance: 15 August 2008

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