Multi-criteria ant system and genetic algorithm for end-of-life decision making
Originally published in the Proceedings of the 2004 Decision Sciences Institute Conference, Boston, Massachusetts, pp. 6371-6376, November 20-23, 2004
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, disassembly-specific concerns. Finding the optimal balance is computationally intensive due to factorial growth. Ant colony optimization and genetic algorithm metaheuristics are presented and compared along with an exa mple to illustrate the implementation. Conclusions drawn include the consistent generation of optimal or near-optimal solutions, the ability to preserve precedence, the speed of the metaheuristics, and their practicality due to ease of implementation.
Surendra M. Gupta and Seamus M. McGovern. "Multi-criteria ant system and genetic algorithm for end-of-life decision making" (2004).
Available at: http://works.bepress.com/smcgovern/7