(687c) Novel Approach for Weighting in Geographic Information System Focused on a Multi-Stakeholder Problem: Case for Residual Biomass Processing System

Geographic Information System (GIS) has proved to be a powerful tool for data management and processing. Recently, GIS has been used to determine suitable location for the design of different manufacturing system, mainly for determining of suitable location. These suitable locations could be obtained considering diverse geographical information layers in order to get enabled or unenabled areas. These geographical layers can be combined through several weights or priorities in a weighted linear combination.

Some methodologies used to determine these weights are the Analytical Hierarchy Process (AHP), Best Worst Method (BWM), or based on knowledge of experts. In this context, it exists a lack of methodologies to determine that weights since in most of them the weights are assigned by subjective or arbitrary manners. It is worth noting that different results (with suitable locations) could be obtained with different weight values. Furthermore, several stakeholders could be associated with each of these obtained results; which would provoke an additional problem to determine the priorities for each stakeholder.

Therefore, this work proposes a novel approach for determining weights in a GIS methodology to find suitable locations where processing plants can be installed based on a multi-stakeholder approach. Our approach consists of mathematical functions formulating for viability and satisfaction for diverse previously obtained GIS models. Consequently, weights are determined via a multi-objective approach to find the tradeoff between objectives. We applied the proposed methodology in a case study for Mexico for optimal determining of locations for residual biomass processing considering corn stover, sugarcane bagasse, sorghum straw, barley straw, wheat straw, agave residue, rice straw and pecan nut shell as raw materials. In addition, case study considers geographical layers such as population level, terrain slope, water bodies location, highways and roads location among others. Finally, four GIS models were generated to be assumed as different stakeholder with different significance factor.

Results show that it is not possible to reach the maximum satisfaction level for each of stakeholders simultaneously; nevertheless, solutions with optimal global satisfaction and suitability are feasible. We generated a Pareto curve to show the compromise between viability and satisfaction; which could be an extra tool for the making decision process.