A hybrid approach for joint optimization of base and extended warranty decisions considering out-of-warranty products

•Proposing a novel model to maximize manufacturer profit in finite horizon.•Optimizing main product's warranty and extended warranty length and price, and spare part price for out-of-warranty products.•A novel hybridization of metaheuristics and dynamic programming algorithm is proposed.•Research outcomes show how changing the life cycle affects the base and extended warranty length. In practice, manufacturers who offer base and extended warranty should make simultaneous decisions on product pricing, spare part pricing for out-of-warranty products, base and extended warranty policy, and spare part inventory management. Previous studies neither considered the influence of out-of-warranty products as one of the main sources of manufacturers’ profit nor optimized these decisions in an integrated model. In this paper, these challenges are addressed by introducing an optimization model to maximize the manufacturer's profit. A new math-heuristic algorithm is proposed for solving the model using the hybridization of metaheuristic algorithms with a developed dynamic programming algorithm. To generate a new solution within the loop of the metaheuristic algorithm, the product price, spare part price and warranty policy variables are first determined with the aid of the operators of league championship algorithm or improved particle swarm optimization algorithm. The maximum number of failures in each time interval is calculated accordingly, and finally, spare part inventory costs are optimized with the aid of the proposed dynamic programming algorithm. The model is verified by Monte-Carlo simulation and is solved with real data for LED TV product. A sensitivity analysis is conducted to evaluate the influence that various parameters may have on the optimal solution.