Concerns about the environmental impact of transportation and logistic activities have greatly increased in recent years. Since integrated operations can help achieve goals of lesser harm to the environment, while remaining operational effective (Qiu et al., 2017), supply chain optimization problems have attracted much research efforts. Among these problems, the production routing problem (PRP) that jointly optimizes decisions of production, inventory, distribution and routing has recently received a considerable attention (Adulyasak et al., 2015a). This integrated optimization problem is of practical relevance to success in business competitions, especially in modern logistical practices of vendor managed inventory (VMI) and just-in-time (JIT). Besides integrating operations forward, closed-loop supply chain optimization showed a further reduction in environmental impact (Savaskan et al., 2004). Return flow processes in a closed-loop supply chain usually consists of (1) product collection from consumers; (2) reverse logistics to take collected products back; (3) screening, assorting and disposal to specify the most economically attractive reuse alternatives; (4) remanufacturing; and (5) remarketing to produce and utilize new markets (Iassinovskaia et al., 2017). A closed-loop PRP naturally integrates reverse logistics and remanufacturing. This problem is important because in addition to economic benefits, environmental benefits due to extension of the product useful life, reduced energy and material consumption, pollution prevention, and other sustainability benefits can be expected. After the importance of considering production, inventory and routing decisions simultaneously was stressed by Chandra (1993), the PRP was extended in various ways to consider, e.g., multiple plants and heterogeneous fleets of vehicles (Lei et al., 2006), incapacitated production (Archetti et al., 2011), multiple homogeneous capacitated vehicles (Adulyasak et al., 2014a), demand uncertainty (Adulyasak et al., 2015b), multi-item back-order (Brahimi and Aouam, 2015), perishable products(Vahdani et al., 2017), and multiscale production(Zhang et al., 2017) in the past decade. The environmental impact of the PRP has seldom been addressed, with only a few notable exceptions, such as the PRP with carbon emissions (Qiu et al., 2017), and multi-objective production and pollution routing problem with time window (Kumar et al., 2015). However, reverse logistics and remanufacturing are completely ignored to the best of our knowledge. Battarra et al. (2014) addressed pickup-and-delivery problems for goods transportation, and reviewed various available algorithms. The vehicle routing problem with simultaneous pickups and delivery (VRPSPD), also known as the most studied and most general variant of the one-to-many-to-one (1-M-1) problems, has become increasingly popular. The electric appliances industry, beverage industry, and returnable/reusable transport items (RTI), or returnable/reusable logistical packaging have witnessed the application of the VRPSPD. Exact algorithms such as branch-and-cut method (Subramanian et al., 2013), branch-price-and-cut method (Cherkesly et al., 2015; Qu and Bard, 2015), are relatively new. Inventory routing problems with simultaneous pickups and deliveries (IRPSPD) have been explored only recently (Soysal, 2016; van Anholt et al., 2016; Iassinovskaia et al., 2017). Extending these problems and methods to the PRP is a natural step forward.