Recently the optimisation of end-of-life (EOL) computer remanufacturing has been highlighted since a big amount of used computers have been disposed of every year. Each part inspected after disassembling EOL computers can have various EOL options such as reuse, repair, reconditioning and so on. Depending on EOL options, recovered values and costs of parts will be different. Hence, in order to maximise the profit of remanufactured computers, it is important to develop the method as to how to decide the EOL options of computer parts. To this end, this study deals with a decision-making problem to select the best EOL option policy of the computer parts for maximising the total profit of computer remanufacturing considering its incurred costs and demand of remanufactured computers during multiple production periods. In particular, to maximise the total profit, the conditional repair option is newly proposed. To resolve the problem, a genetic search algorithm and an ant colony search algorithm have been developed. Computational experiments have carried out to evaluate the algorithms and the proposed conditional repair option.