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The growing amount of waste created by products reaching the end of their useful lives poses challenges for the environment, governments and manufacturers. Processing alternatives include reuse, remanufacturing, recycling, storage and disposal. With disposal considered the least desirable, the first process required by the remaining alternatives is disassembly. Just as the assembly line is considered the most efficient way to assemble a product, the disassembly line is the most efficient way to disassemble a product. Finding the optimal balance for the multi-objective disassembly line balancing problem is computationally intensive due to exponential growth. With exhaustive search calculations quickly becoming prohibitively large, methodologies from the field of combinatorial optimization hold promise for providing solutions. The disassembly line balancing problem is described here, then defined mathematically and proven to belong to the class of unary NP-complete problems. Known optimal instances of the problem are developed, then disassembly line versions of exhaustive search, genetic algorithm and ant colony optimization metaheuristics, a greedy algorithm, and greedy/ hill-climbing and greedy/2-optimal hybrid heuristics are presented and compared along with a novel uninformed general-purpose search heuristic.