Abstract
This paper develops a benchmarking framework to support performance-based sunshine regulation in the water sector. It uses benefit-of-the-doubt composite indicators formulated with a directional distance function. Weight restrictions are incorporated in the model to account for different perspectives in the performance assessment. The framework is tested using data of the Portuguese regulation authority concerning the activity of wastewater operators. The information obtained using this framework reflects overall performance at the firm level and complements traditional evaluations of regulatory authorities based on the analysis of individual indicators. The results can be used to disseminate best practices, motivate continuous improvement, and foster enhancements in the governance of regulated utilities.

Abstract
Soybean is one of the main sources of protein directly and indirectly in human nutrition, and it is highly dependent on logistics to connect country growers and international markets. Although recent studies deal with the impact of logistics on international trade, this impact in agricultural commodities is still an open research question. Moreover, these studies usually do not consider the influence of all components of the logistics on trade. This paper, therefore, aims at identifying the role of logistics performance in soybean exports among Argentina, Brazil, the US and their trading partners from 2012 to 2018. Using an extended gravity model, we examine whether the indicators of the World Bank Logistics Performance Index (LPI), adopted as a proxy of logistics efficiency, are an important determinant of bilateral soybean trade facilitation. The results lead to the conclusion that it is necessary to analyze the LPI throughout its indicators because they may affect trade differently. The novelty of this article is to provide an analysis of the impact of different logistics aspects on commodity trade, more specifically in the soybean case. Finally, regarding the model results, logistics infrastructure has a positive and significant correlation with soybean trade as supposed in most of the literature.

Abstract
In this paper, we propose an innovative approach to integrate the wastewater treatment (WWT) that is carried out in a set of plants and the anaerobic digestion (AD) that is carried out in a different set of plants, all from the same system. The aim is to contribute to sustainability improvements (e.g., cost reduction and environmental and social benefits) within the system. The main drivers that support this approach are the existence of unutilized capacity in some digesters and the possibility of reducing the process sludge age to maintain its biogas potential during the aerobic treatment in the plants without AD facilities. Furthermore, the effect of co-digestion as a means of enhancing the amount of biogas that can be produced through the sludge is also considered. This innovative approach leads to a mixed-integer linear programming (MILP) model to optimize the sludge flows that connect the plants without AD facilities to the ones with anaerobic digesters. The developed approach was applied to a Portuguese water utility and the results provide new insights for an optimized sludge management process of WWTPs, also indicating that the economic benefit obtained from the proposed strategy for sludge management can lead to a reduction of up to 23.5% in terms of current energy costs.

Abstract
Algorithmic systems based on artificial intelligence (AI) increasingly play a role in decision-making processes, both in government and industry. These systems are used in areas such as retail, finances, and manufacturing. In the latter domain, the main priority is that the solutions are interpretable, as this characteristic correlates to the adoption rate of users (e.g., schedulers). However, more recently, these systems have been applied in areas of public interest, such as education, health, public administration, and criminal justice. The adoption of these systems in this domain, in particular the data-driven decision models, has raised questions about the risks associated with this technology, from which ethical problems may emerge. We analyse two important characteristics, interpretability and trustability, of AI-based systems in the industrial and public domains, respectively.

Abstract
Manufacturing environments commonly present uncertainties and unexpected schedule disruptions. The literature has shown that in these environments simple and fast dynamic dispatching rules are efficient sequencing methods. However, most of the works in the automated designing of these rules have considered deterministic processing times. This work aims to design dispatching rules for problem settings similar to the ones found in real environments such as uncertain processing times and sequence-dependent setup times. We use Genetic Programming to generate efficient rules for stochastic job shops with setup times. We show that the generated rules outperform benchmark dispatching rules, specially in settings with high setup time levels. © 2020, Springer Nature Switzerland AG.

Abstract
We present a natural probabilistic variation of the multi-depot vehicle routing problem with pickup and delivery (MDVRPPD). In this paper, we present a variation of this deterministic problem, where each pair of pickup and delivery points are present with some probability, and their realization are only known after the routes are computed. We denote this stochastic version by S-MDVRPPD. One route for each depot must be computed satisfying precedence constraints, where each pickup point must appear before its delivery pair in the route. The objective is to find a solution with minimum expected traveling distance. We present a closed-form expression to compute the expected length of an a priori route under general probabilistic assumptions. To solve the S-MDVRPPD we propose an Iterated Local Search (ILS) that uses the Variable Neighborhood Descent (VND) as local search procedure. The proposed heuristic was compared with a Tabu Search (TS) algorithm based on a previous work. We evaluate the performance of these heuristics on a data set adapted from TSPLIB instances. The results show that the ILS proposed is efficient and effective to solve S-MDVRPPD. © 2020 Polish Information Processing Society - as it is since 2011.