This research develops a novel MCDM approach that combines the ordinal priority approach (OPA) and a weighted influence nonlinear gauge system (WINGS), for policy making about undergraduate programs and specifically elective courses. We interviewed eight professors at the School of Engineering, Universidad Catolica del Norte, who are highly engaged in organizing elective courses to obtain their prioritization criteria for offering them to undergraduate students. We proposed and applied an MCDM approach based on OPA-WINGS to rank criteria that make the process of planning future electives courses to offer more straightforward. We found that scientific thinking, Industries’ needs, and the School’s research lines are the main criteria for designing a new elective class. We conducted a sensitivity analysis to demonstrate de robustness of the suggested measures. This work illustrates how OPA-WINGS can improve decision-making for offering elective courses. The results indicate that Industries’ needs and School’s research lines strongly impact undergraduate programs’ direction.

This research is about developing a decision support system (DSS) for the distribution of grapes and grape must in a Chilean cooperative, Cooperativa Agrícola Pisquera Elqui Limitada (CAPEL). CAPEL is dedicated to producing and distributing several beverages such as sparkling wines, beers, energy drinks, rum, and pisco. This work aims to support the grinding‐related transport stage through a linear programming based DSS, in order to find the optimal use of the transport demand in a network based on source and destination plants during the harvest season. To achieve this aim, an operational research (OR) model that feeds the DSS is developed, whose objective function seeks to minimize the total transport cost. The decision variables define the grape cargo to be transported from a source plant to a destination plant. The OR model uses constraints such as transportation demand, grinding capacity, maximum storage, and available grape in plants. The model succeeded in reducing the total transport costs by 14% for the 2017 season of the pisco‐making process, meaning approximately savings of 59 million Chilean pesos.

Chile is among the largest walnut producers and exporters globally, thanks to a favorable nut growth and production environment. Despite an increasingly competitive market, the literature offers little scientific advice regarding decision support systems (DSSs) for the nut sector. In particular, the literature does not present optimization approaches to support decision-making in walnut supply chain management, especially the processing planning. This work provides a DSS that allows the exporter to plan walnut processing decisions taking into account the quality of the raw material, such as size, color, variety, and external and internal defects, in order to maximize the benefits of the business. To formalize the problem, an integer programming model is proposed. The DSS was implemented via a web application for MeliFen, a walnut exporter located near Santiago, Chile. A comparative analysis of the last two years revealed that MeliFen increased its profit by approximately 9.8% using this tool. We also suggest other uses that this DSS provides, besides profit maximization.