This article presents a general multi-objective mixed-integer linear programming (MILP) optimizationmodel aimed at providing decision support for waste and resources management in industrial networks.The MILP model combines material flow analysis, process models of waste treatments and other industrialprocesses, life cycle assessment, and mathematical optimization techniques within a unified framework.The optimization is based on a simplified representation of industrial networks that makes use of lin-ear process models to describe the flows of mass and energy. Waste-specific characteristics, e.g. heatingvalue or heavy metal contamination, are considered explicitly along with potential technologies or pro-cess configurations. The systems perspective, including both provision of waste treatment and industrialproduction, enables constraints imposed upon the systems, e.g. available treatment capacities, to beexplicitly considered in the model. The model output is a set of alternative system configurations interms of distribution of waste and resources that optimize environmental and economic performance.The MILP also enables quantification of the improvement potential compared to a given reference state.Trade-offs between conflicting objectives are identified through the generation of a set of Pareto-efficientsolutions. This information supports the decision making process by revealing the quantified performanceof the efficient trade-offs without relying on weighting being expressed prior to the analysis. Key featuresof the modeling approach are illustrated in a hypothetical case. The optimization model described in thisarticle is applied in a subsequent paper (Part II) to assess and optimize the thermal treatment of sewagesludge in a region in Switzerland.