Disassembly takes place in remanufacturing, recycling and disposal, with a line being the best choice for automation. The disassembly line balancing problem seeks a sequence which: is feasible, minimizes workstations, and ensures similar idle times, as well as other end-of-life specific concerns. Finding the optimal balance is computationally intensive due to exponential growth. Combinatorial optimization methods hold promise for providing solutions to the disassembly line balancing problem, which is proven here to belong to the class of unary NP-complete problems. Probabilistic (ant colony optimization) and uninformed (H-K) search methods are presented and compared. Numerical results are obtained using a recent case study to illustrate the search implementations and compare their performance. Conclusions drawn include the consistent generation of near-optimal solutions, the ability to preserve precedence, the speed of the techniques, and their practicality due to ease of implementation.


Originally published in the Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing V, Boston, Massachusetts, pp. 81-92, October 23-24, 2005


Disassembly, product recovery, complexity theory, ant colony optimization, Hunter-Killer (H-K) general-purpose heuristic, combinatorial optimization, disassembly line balancing

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Copyright 2005, Society of Photo-Optical Instrumentation Engineers


This paper was published in Proceedings of SPIE (Volume 5997) and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

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