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BACKGROUND: The huge industrial growth of recent decades has led to the production of significant amounts of by-product streams. The appropriate use of these by-product streams can offer benefits either socially, by producing high quality products, or environmentally, by avoiding the excessive use of natural resources and reducing their impact on natural ecosystems. Technology selection at a strategic level is among the most challenging problems in many areas of science and engineering. RESULTS: A case study is considered, in which 300 kt year −1 of monosaccharides are assumed available to produce a spectrum of potential bio-based products. In an optimal situation, all raw material is utilized for the production of bio-succinic acid with a manufacturing cost of 522.3 M$ year −1 , revenue of 747 M$ year −1 and a net present value (NPV) of M$1482.4. When less than 50% of the raw material can be utilized by any of the available technologies, the algorithm selects the simultaneous production of succinic acid and methyl-ethyl-ketone and the NPV is reduced to M$1360. Finally, when each technology cannot use more than 1/8 of the available raw material, five out the eight potential technologies are selected, which end up consuming 62.5% of the available raw material while the NPV is reduced significantly to M$497. CONCLUSION: A novel and practically useful mathematical programming method, that can be used to assist in making decisions related to a long-term planning of biotechnological production processes using renewable raw materials, is proposed in this work and its advantages are demonstrated through a large-scale case study.