In this paper, a new formulation is presented for the optimal scheduling of industrial supply chains. This is accomplished through the development of a master representation model, the ChainSTN, that unambiguously describes the supply chain topology, resources, operations, and involved materials. Also, different market opportunities (supply, demand, and price options) and manufacturing and transport considerations are regarded. By combining these concepts with a discrete and uniform representation of the scheduling time domain, a mixed-integer linear programming formulation (MILP) is attained. A detailed optimal scheduling plan is obtained, where different (i) operational decisions, describing the operations of the entire partners network; (ii) transportation policies, detailing the material flows among partners; and (iii) market options (provider's conditions and customers' demand orders) are jointly scheduled so as to optimize a global economical criterion, in here, the supply chain global profit. The flexibility and applicability of the new formulation are validated through the solution of an industrial example where different operational scenarios are discussed.