In 2011, FAO estimated that about one third of the total production of edible food for human consumption, gets lost or wasted, globally. In industrialized countries, more than 40% of the food losses occur at retail and consumer levels. A considerable part of the wasted food can be reused. The SORT project aims at ``recycling'' food in excess by converting it into animal feed or fuel for biogas/biomass power plants. During this process of reconditioning it is necessary to make choices in order to minimize the costs and maximize the earnings. However, due to the extremely complex nature of the process, it is not possible for a human being to make these choices at runtime and in an optimal manner. In these cases, Decision Support Systems (DSS) can be of help. In this paper we propose a DSS based on the Constraint Logic Programming (CLP) paradigm and ontology reasoning for finding the optimal solution. The information about feed processing and feed categories were extracted from Regulation (EU) 2017/1017 and stored into an ontology. Finally, we provide an evaluation of our system on several synthetic datasets with different search settings.
A Decision Support System for Food Recycling based on Constraint Logic Programming and Ontological Reasoning
Federico ChesaniPrimo
;Evelina Lamma;Paola Mello;Fabrizio RiguzziUltimo
2018
Abstract
In 2011, FAO estimated that about one third of the total production of edible food for human consumption, gets lost or wasted, globally. In industrialized countries, more than 40% of the food losses occur at retail and consumer levels. A considerable part of the wasted food can be reused. The SORT project aims at ``recycling'' food in excess by converting it into animal feed or fuel for biogas/biomass power plants. During this process of reconditioning it is necessary to make choices in order to minimize the costs and maximize the earnings. However, due to the extremely complex nature of the process, it is not possible for a human being to make these choices at runtime and in an optimal manner. In these cases, Decision Support Systems (DSS) can be of help. In this paper we propose a DSS based on the Constraint Logic Programming (CLP) paradigm and ontology reasoning for finding the optimal solution. The information about feed processing and feed categories were extracted from Regulation (EU) 2017/1017 and stored into an ontology. Finally, we provide an evaluation of our system on several synthetic datasets with different search settings.File | Dimensione | Formato | |
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