Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach

Lean and agile principles have attracted considerable interest in the past few decades. Industrial sectors throughout the world are upgrading to these principles to enhance their performance, since they have been proven to be efficient in handling supply chains. However, the present market trend demands a more robust strategy incorporating the salient features of both lean and agile principles. Inspired by these, the leagility principle has emerged, encapsulating both lean and agile features. The present work proposes a leagile supply chain based model for manufacturing industries. The paper emphasizes the various aspects of leagile supply chain modeling and implementation and proposes a new Hybrid Chaos-based Fast Genetic Tabu Simulated Annealing (CFGTSA) algorithm to solve the complex scheduling problem prevailing in the leagile environment. The proposed CFGTSA algorithm is compared with the GA, SA, TS and Hybrid Tabu SA algorithms to demonstrate its efficacy in handling complex scheduling problems

Simulation modelling is 50! Do we need a reality check?

imulation modelling is a fascinating research field. The techniques and tools of simulation modelling have been used to research and investigate the behaviour of various systems in a wide range of areas such as commerce, computer networks, defence, health, manufacturing and transportation. Indeed, the study of the use of these techniques and tools, and the development of new forms of these, are a rich source of research in their own right. Simulation modelling is about to reach the 50th anniversary of the development of GSP (General Simulation Program), the first simulation modelling language (Tocher and Owen, 1960). There have been several historical accounts of simulation modelling research. To complement these, we have performed a review of the recent history of simulation modelling. This study targeted three leading journals dedicated to this field. These are the ACM Transactions of Modeling and Computer Simulation, Simulation: Transactions of The Society for Modeling and Simulation International and Simulation Modelling Practice and Theory (formerly Simulation Practice and Theory). The study covered the first 6 years of this century (2000–2005) and included 576 papers. The key observation of this work was the relative lack of 'real world' involvement in simulation modelling research and an even greater lack of evidence of 'real world' benefit, arguably very alarming outcomes for an applied field. To further investigate this observation two additional surveys were carried out, one to study if real world papers appeared in the more widely known OR/MS literature (837 papers in 12 journals) and one to study if such papers appeared in Manufacturing and Logistics, an application area closely associated with simulation modelling (1077 papers in 10 journals). The results of these surveys confirmed our observations. We ask if this is the natural evolution of a field that has existed for half a century or an indication of a worrying problem? This paper reports on our findings and discusses whether or not simulation modelling research urgently needs to face a 'reality check.

Bullwhip and backlash in supply pipelines.

'Bullwhip' is the phenomenon experienced in practice, signifying the propagation and amplification of orders as they pass upstream in a supply chain pipeline. 'Bullwhip' creates uncertainty for managers who then create stock and/or maintain excess capacity leading to increased total costs. A well known descriptor of the phenomenon is the MIT Beer Game simulation. We use the Beer Game to describe and explore a different phenomenon we term the 'backlash' effect. This is the resulting impact of the 'bullwhip' effect on shipments downstream. The two effects described have analogue with amplitude pressure wave propagation ('bullwhip') and reflection ('backlash') in physical systems such as flow ducts. We use the Fourier transform method to describe the 'bullwhip' propagation and 'backlash' reflections. We conclude that the 'backlash' effect occurs due to the ready availability of capacity in the whole supply chain and inventory in the final echelon