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To combat the environmental issues posed by global warming and the depletion of natural resources, the emission of greenhouse gases (GHG) and the consumption of natural resources must be economically reduced. Upgrading and remanufacturing are expected to play important roles in dealing with both issues since they can save the production of virgin materials associated with GHG emissions for assembled products by component reuse and material recycling. Although upgrading components can add additional values and avoid their value obsolescence, composing reused components with shorter physical or value lifetime in a remanufactured product leads to decreasing revenue from selling the upgrade-remanufactured product. Hence, in these cases, component reuse and material recycling can be more economical life cycle option than upgrading and remanufacturing. Furthermore, disassembly is an essential process for recovery options such as upgrading, remanufacturing, components reuse, and material recycling, and tends costly due to the labor costs of manual disassembly. Disposing without disassembly may be a better life cycle option. Therefore, life cycle options, including upgrading, remanufacturing, reusing, recycling and disposal should be suitably selected for each component based on an additional value by upgrading, physical and value lifetimes for each component. This study proposes an upgrade-remanufacturing decision method to maximize GHG saving rate and profit using 0-1 integer programming with ε constraint method. The numerical experiments are conducted using the laptop consisted of 34 components. The results in the laptop indicate that the selling price of upgrade-remanufactured product should be set to more than 2,000 Yen, and the achievement of much higher GHG saving rate such as 99% would lead to negative earnings. Additionally, the bi-objective model is expanded to multi-objective for profit, GHG saving, and recovery rates for investigation of the profit and the selected life cycle options for each component.