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Optimising end-of-life laptop remanufacturing decisions using meta-heuristics

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  • Gurunathan Anandh
  • Shanmugam PrasannaVenkatesan
  • Mark Goh
  • Gyan Chandra Kushwaha

Abstract

As the lifecycle of a laptop gets shorter, the world should expect more end-of-life (EOL) laptops. Remanufacturing of laptops is viewed as the best EOL alternative for environmental and societal reasons. This research uses a multi-period nonlinear integer programming model to decide the best EOL options for the remanufactured laptop parts based on their quality. Discrete particle swarm optimisation (DPSO) and genetic algorithm (GA) are implemented as a decision support tool in Microsoft Excel to yield the near-optimal solution. Numerical tests are conducted to compare the effectiveness of the two algorithms. For small-sized problems, the solution of the algorithms is compared with the global optimal solution obtained by the full enumeration method. For large problem instances, the solution obtained using the algorithms is compared with each other. A sensitivity analysis is performed to study the impact of the shortage and repair costs and demand on profit.

Suggested Citation

  • Gurunathan Anandh & Shanmugam PrasannaVenkatesan & Mark Goh & Gyan Chandra Kushwaha, 2025. "Optimising end-of-life laptop remanufacturing decisions using meta-heuristics," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 53(4), pages 525-555.
    • Handle: RePEc:ids:ijores:v:53:y:2025:i:4:p:525-555
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