A General Simulation Framework for Supply Chain Modeling: State of the Art and Case Study

Nowadays there is a large availability of discrete event simulation software that can be easily used in different domains: from industry to supply chain, from healthcare to business management, from training to complex systems design. Simulation engines of commercial discrete event simulation software use specific rules and logics for simulation time and events management. Difficulties and limitations come up when commercial discrete event simulation software are used for modeling complex real world-systems (i.e. supply chains, industrial plants). The objective of this paper is twofold: first a state of the art on commercial discrete event simulation software and an overview on discrete event simulation models development by using general purpose programming languages are presented; then a Supply Chain Order Performance Simulator (SCOPS, developed in C++) for investigating the inventory management problem along the supply chain under different supply chain scenarios is proposed to readers.

[1]  V. P. Babich,et al.  An approach to compiler construction for a general-purpose simulation language , 1991 .

[2]  David J. Thuente Critique of SIMAN as a programming language (abstract only) , 1987, CSC '87.

[3]  Ezekiel Okike,et al.  AN EVALUATION OF CHIDAMBER AND KEMERER'S LACK OF COHESION IN METHOD (LCOM) METRIC USING DIFFERENT NORMALIZATION APPROACHES , 2008 .

[4]  Francesco Longo,et al.  An advanced supply chain management tool based on modeling and simulation , 2008, Comput. Ind. Eng..

[5]  Agostino G. Bruzzone Preface to Modeling and Simulation Methodologies for Logistics and Manufacturing Optimization , 2004, Simul..

[6]  J. Banks,et al.  Handbook of Simulation , 1998 .

[7]  Moshe Y. Vardi,et al.  Verification , 1917, Handbook of Automata Theory.

[8]  Chris F. Kemerer,et al.  A Metrics Suite for Object Oriented Design , 2015, IEEE Trans. Software Eng..

[9]  Francesco Longo,et al.  Inventory and internal logistics management as critical factors affecting the supply chain performances , 2009, Int. J. Simul. Process. Model..

[10]  G. De Sensi,et al.  Inventory policies analysis under demand patterns and lead times constraints in a real supply chain , 2008 .

[11]  Michael Pidd,et al.  Using Java to develop discrete event simulations , 2000, J. Oper. Res. Soc..

[12]  George S. Fishman,et al.  Discrete-Event Simulation : Modeling, Programming, and Analysis , 2001 .

[13]  John S. Carson AutoStat: output statistical analysis for AutoMod users , 1996, Winter Simulation Conference.

[14]  Osman Balci,et al.  Verification, Validation, and Testing , 2007 .

[15]  Taryana Suryana Borland C++ Builder , 2009 .

[16]  Jerry Banks,et al.  Handbook of simulation - principles, methodology, advances, applications, and practice , 1998, A Wiley-Interscience publication.

[17]  Vlatka Hlupic Discrete-Event Simulation Software: What the Users Want , 1999, Simul..