SALBPGen - A systematic data generator for (simple) assembly line balancing
AbstractAssembly line balancing is a well-known and extensively researched decision problem which arises when assembly line production systems are designed and operated. A large variety of real-world problem variations and elaborate solution methods were developed and presented in the academic literature in the past 60 years. Nevertheless, computational experiments examining and comparing the performance of solution procedures were mostly based on very limited data sets unsystematically collected from the literature and from some real-world cases. In particular, the precedence graphs used as the basis of former tests are limited in number and characteristics. As a consequence, former performance analyses suffer from a lack of systematics and statistical evidence. In this article, we propose SALPBGen, a new instance generator for the simple assembly line balancing problem (SALBP) which can be applied to any other assembly line balancing problem, too. It is able to systematically create instances with very diverse structures under full control of the experiment's designer. In particular, based on our analysis of real-world problems from automotive and related industries, typical substructures of the precedence graph like chains, bottlenecks and modules can be generated and combined as required based on a detailed analysis of graph structures and structure measures like the order strength. We also present a collection of new challenging benchmark data sets which are suited for comprehensive statistical tests in comparative studies of solution methods for SALBP and generalized problems as well. Researchers are invited to participate in a challenge to solve these new problem instances.
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Bibliographic InfoPaper provided by Friedrich-Schiller-University Jena, School of Economics and Business Administration in its series Jena Research Papers in Business and Economics - Working and Discussion Papers with number 05/2011.
Date of creation: 23 May 2011
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