We propose a parallel portfolio of metaheuristic algorithms that adopts a market trading-based time allocation mechanism. This mechanism dynamically allocates the total available execution time of the portfolio by favoring better-performing algorithms. The proposed approach is assessed on a significant Operations Research problem, namely the single-item lot sizing problem with returns and remanufacturing. Experimental evidence suggests that our approach is highly competitive with standard metaheuristics and specialized state-of-the-art algorithms.