Abstract

ABSTRACT The growing diversity in demand and the shorter life cycle of products necessitate integrating policies of design, production, and marketing to decide on which products, with which attributes should be designed and by which strategies should be supplied to the market. This necessity increases in the manufacturing of the Configurable Products Family (CPF) such as cars, laptops, cell phones. The existing decision-making models either do not deal with all the three policies or are not concerned with the main variables. This study aims to develop a profit maximization model to integrate policies for CPFs by optimizing the main variables: the product’s configuration, supply policy of components, price, and warranty lengths for product’s modules. A new demand function is developed for such decision-making as well. The model is mixed-integer nonlinear programming, so an adapted Particle Swarm Optimization (PSO) is applied to solve different numerical cases and perform several sensitivity analysis. The results depict significant changes in the company’s policy and profitability due to applying the model. The findings can introduce new insights for managers and engineers and a focal point for researchers to run further studies.

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