Many supply chains suffer from a lack of flexibility, adaptability, and robustness, which imposes customer dissatisfaction, transportation, backlog, and rework costs on companies. The mobile supply chain (MSC) is a newly developed idea that aims to rectify this problem. In this kind of supply chain, production, distribution, and delivery of a product family are performed by a mobile factory (MF), which can be carried by truck, while stationary production sites are no longer required. The production process is completed directly at the customer's location following customer detail requirements. In this paper, a mathematical model is developed to optimize the mobile factory routing problem as well as production scheduling at each customer's site, which is inspired by a real-world application of modular production in the chemical industry. For this purpose, due dates of customers’ work orders and transportation costs should be considered simultaneously. The model results indicate that if these objective functions are taken into account separately, the results will be sub-optimal solutions causing substantial financial losses for customers and suppliers. The proposed bi-objective model using a multi-objective optimization approach proffers a Pareto frontier. Accordingly, decision-makers can choose from a range of solutions, from zero delayed orders to the lowest transportation costs. However, in many cases it is possible to reach zero delayed orders with just a small increase in transportation costs.