This study examines how support interventions for Circular Food Economy (CFE) implementation can be prioritized when agri-food firms face different barriers and support needs. Using survey data from 100 food-related industry respondents in Japan, it identifies current food loss and waste practices, implementation barriers, and preferred support interventions. These findings are translated into the CFE Support Intervention Prioritization (CFE-SIP) model, which evaluates seven intervention alternatives across seven criteria. The decision problem is examined through theoretical scenario analysis and an exploratory FITradeoff application. The results show that intervention priorities differ from those based solely on respondents stated preferences, indicating that effective support design should also consider broader strategic implementation criteria. The study contributes a decision-support framework for translating stakeholder evidence into structured intervention priorities. Because the survey is exploratory and some criterion evaluations rely on structured judgment, the results should be interpreted as a demonstration of the framework rather than as universally applicable rankings for all agri-food firms.
Purpose: this paper proposes a decision model to prioritize international cooperation partners in net-zero technology development, integrating the structure of the global collaboration network with the technological maturity of national project portfolios. Methodology: a two-stage approach is applied to the IEA ETP Clean Energy Technology Guide database. First, 168 multinational projects are modeled as a collaboration network (53 countries, 470 ties), from which degree and eigenvector centralities are computed. Second, the fifteen most connected countries are evaluated with PROMETHEE II on three criteria—degree centrality, eigenvector centrality and average Technology Readiness Level (TRL)—under five weighting scenarios, including entropy-based objective weights, with TOPSIS used as a cross-method robustness comparison. Findings: degree centrality and average TRL are negatively correlated (Spearman ρ = −0.66, p < 0.01), showing that structural prominence and portfolio maturity are conflicting criteria and that single-metric prioritization is misleading. The United States, Germany, Japan, the Netherlands and China lead the baseline ranking, while maturity-oriented preferences promote South Korea, Canada and Denmark; the rankings are conditional on the weighting scenarios but largely stable across scenarios, aggregation methods and compositions of the alternative set (ρ = 0.85 between PROMETHEE II and TOPSIS). Originality/value: to the best of our knowledge, this is the first outranking-based partner-prioritization model that uses graph centralities and TRL jointly as criteria in the net-zero context, providing scenario-based decision support for energy-innovation cooperation policy.
The planning of sports facilities involves allocating limited public resources among competing territorial demands while considering multiple planning objectives. Previous studies have extensively examined accessibility, spatial equity, and infrastructure availability, but less attention has been given to decision-support frameworks for actual resource allocation. To address this gap, this study proposes the Multicriteria Allocation of Resources System for Utility Maximization (MARS-UM), a decision-support system (DSS) that integrates harmonious multiobjective optimization and non-local search for sports facility investment planning. MARS-UM was implemented as a web-based computing module and applied to 80 planning areas in Belo Horizonte, Brazil. Two investment scenarios were evaluated, with budgets of R10 million and R20 million. Results show that MARS-UM consistently prioritized territories with lower levels of sports infrastructure availability. Statistical analyses revealed significant differences between selected and non-selected areas across most infrastructure categories, with effect sizes indicating substantial practical relevance. Spatial analyses further confirmed a strong correspondence between selected territories and infrastructure deficits. The prioritization pattern remained consistent across budget scenarios, while the larger budget expanded the coverage of infrastructure-deficient areas. A benchmark using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) further supported the evaluation of the proposed approach under the same allocation constraints. The study contributes to the literature by moving beyond infrastructure assessment toward actionable resource allocation and provides a transparent and analytically grounded DSS for public investment planning.
Sustainability assessment in agricultural cooperatives requires context-sensitive indicators capable of capturing economic viability, environmental performance, social contribution, and governance practices, especially in regions exposed to climate vulnerability and resource scarcity. This paper aims to select and validate sustainability indicators for agricultural cooperatives in Paraíba, Brazil, with emphasis on the Brazilian Semiarid context. Starting from 78 indicators identified in the literature and organized into five dimensions (economic, environmental, social, specific, and commercial relations), we applied the Fuzzy Delphi method to incorporate expert judgment and address uncertainty in the indicator screening process. Five experts evaluated each indicator using triangular fuzzy numbers representing minimum, most likely, and maximum relevance values. The assessments were defuzzified using the weighted centroid method. The mean relevance score was used to assess the average relevance attributed by the expert panel, while the coefficient of variation was adopted as the consensus criterion. A Python-based routine was developed to automate data processing, calculate descriptive statistics, filter indicators, generate graphical outputs, and support reproducibility. Using a combined threshold of μ_j≥ 7.0 and CV_j≤ 10% , 34 indicators were retained for the sustainability assessment framework. The selected indicators preserved all five dimensions, with emphasis on financial performance, water management, resource efficiency, pollution control, occupational health and safety, employee qualification, member support, supplier responsibility, and commercial relationships. The results indicate that the Fuzzy Delphi method provides a rigorous and transparent approach for adapting sustainability indicators to regional realities. The study contributes to decision-aiding research by offering a validated indicator base for future multicriteria assessment of agricultural cooperatives in semiarid contexts.
Multiobjective optimization algorithms can be employed to generate Pareto-optimal trajectory alternatives for unmanned aerial vehicle (UAV) path planning. These alternatives are generally assumed to represent deterministic solutions during the subsequent decision-making stage. However, this assumption may not hold when the evaluation includes stochastic trajectory repair procedures. This work investigates the influence of repair-induced variability on the interpretation of Pareto-front approximations for decision-making. Three representative instances are solved using a Multiobjective Evolutionary Algorithm, and the approximation corresponding to the median Hypervolume is selected for detailed analysis. Each Pareto solution is subsequently re-evaluated 31 times through independent executions of the repair procedure to quantify the variability of the resulting objective values and flight trajectories. The results show that repeated repairs of an identical B-spline representation can generate significantly different feasible trajectories, transforming nominal Pareto solutions into distributions of attainable performances. These findings highlight the importance of incorporating solution reliability into post-optimization decision making and motivate uncertainty-aware ranking strategies for stochastic multiobjective optimization problems.
