a particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem文档.pdf

Int J Adv Manuf Technol (2013) 69:197–209 DOI 10.1007/s00170-013-4990-1 ORIGINAL ARTICLE A particle swarm optimization algorithm with neighborhood-based mutation for sequence-dependent disassembly line balancing problem Can B. Kalayci Surendra M. Gupta Received: 19 November 2012 /Accepted: 5 April 2013 /Published online: 28 April 2013 # Springer-Verlag London 2013 Abstract For environmentally conscious and sustainable mutation operator is proposed to solve the SDDLBP. Case manufacturing, manufacturers need to incorporate product scenarios are considered, and comparisons with ant colony recovery by designing manufacturing systems to include optimization, river formation dynamics, and tabu search reverse manufacturing by considering both assembly and approaches are provided to demonstrate the superior func- disassembly systems. Just as the assembly line is considered tionality of the proposed algorithm. the most efficient way to assemble a product, the disassem- bly line is seen to be the most efficient way to disassemble a Keywords Product recovery . Disassembly . product. While having some similarities to assembly, disas- Sequence-dependent disassembly line balancing . sembly is not the reverse of the assembly process. The Metaheuristics . Particle swarm optimization . challenge lies in the fact that it possesses unique character- Neighborhood-based mutation istics. In this paper, we consider a sequence-dependent dis- assembly line balancing problem (SDDLBP) that is concerned with the assignment of disassembly tasks to a 1 Introduction set of ordered disassembly workstations while satisfying the disassembly precedence constraints and optimizing the End-of-life (EOL) processing of products is becoming increas- effectiveness of several measures considering sequenc