A genetic algorithm for the optimisation of assembly sequences Romeo M. Marian * , Lee H.S. Luong, Kazem Abhary School of Advanced Manufacturing and Mechanical Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia Available online 10 August 2006 Abstract This paper describes a Genetic Algorithm (GA) designed to optimise the Assembly Sequence Planning Problem (ASPP), an extremely diverse, large scale and highly constrained combinatorial problem. The modelling of the ASPP problem, which has to be able to encode any industrial-size product with realistic constraints, and the GA have been designed to accommodate any type of assembly plan and component. A number of specific modelling issues necessary for understand- ing the manner in which the algorithm works and how it relates to real-life problems, are succinctly presented, as they have to be taken into account/adapted/solved prior to Solving and Optimising (S/O) the problem. The GA has a classical struc- ture but modified genetic operators, to avoid the combinatorial explosion. It works only with feasible assembly sequences and has the ability to search the entire solution space of full-scale, unabridged problems of industrial size. A case study illustrates the application of the proposed GA for a 25-components product. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: Assembly sequence planning; Representation; Precedence relations; Genetic algorithms; Genetic operators; Combinatorial optimisation 1. Introduction Assembly is an obligatory process for all multi-component manufactured goods. Assembly contributes sig- nificantly to both cost and lead-time of a product (20–50%, sometimes even more (Nof, Wilbert, & Warnecke, 1997), approaching an astounding 90% in specific areas in micro-technologies and electronics). Assembly Sequence Planning is part of Assembly Planning. An assembly sequence is the most important part of an assembly plan and it affects other aspects of the assembly process – resources, assembly line layout, efficiency and cost – as well as various details in the product design. Automating the generation of assembly sequences and their optimisation can ensure the competitivity of manufactured goods and increase profit margins. This paper focuses on a GA designed to optimise the assembly sequence of any type of mechanical products for problems of industrial size by overcoming the difficulties associated with the size and character of the ASPP. Other, associated aspects, necessary for the understanding of the manner in which the algorithm works 0360-8352/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.cie.2005.07.007 * Corresponding author. Tel.: +618 83025275; fax: +618 83023380. E-mail address: romeo.marian@unisa.edu.au (R.M. Marian). Computers & Industrial Engineering 50 (2006) 503–527 www.elsevier.com/locate/dsw