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Closed-loop supply chain (CLSC), as an important branch of supply chain, has received increasing attention in recent decades. However, CLSC for perishable food products that is more complex than classic CLSC has been seldom studied in spite of its growing applications in practice. This thesis aims to develop new models and methods for optimizing closed-loop food supply chain with returnable transport items. To this end, three new problems are investigated.Firstly, a closed-loop food supply chain with returnable transport items (CLFSC-RTI) is studied. This problem involves a single manufacturer and a single retailer. Outsourcing is permitted and RTI purchasing budget is limited. The objective is to maximize the total profit of the supply chain. The problem is formulated as a mixed integer linear program (MILP) and it is proved to be NP hard. To solve the problem, an improved kernel search-based heuristic is designed. Computational experiments on a real case study and extensive random instances demonstrate the effectiveness and efficiency of the proposed model and heuristic.Secondly, a bi-objective closed-loop food supply chain with returnable transport items (BCLFSC-RTI) is investigated. The two objectives are to maximize the total profit and to minimize carbon emissions, simultaneously. The studied problem considers multiple retailers. For this complex bi objective problem, a bi-objective MILP is proposed for its modelling, and an iterative ε-constraint method is applied to solve it. Then, an improved kernel search-based heuristic is developed to solve the transformed single objective problem in each iteration of the ε-constraint method. Computational results based on various randomly generated instances show that the performance of the proposed method is comparable to that of a state-of-the-art commercial optimization solver CPLEX.Finally, a closed-loop food inventory-routing problem with RTIs (CFIRP-RTI) is addressed. In this problem, a vehicle routing problem is integrated and returnable transport items with different protective levels are considered. An appropriate MILP is proposed to formulate the problem, and the problem is proved to be NP-hard. Numerical experiments are carried out to validate the proposed model., La chaîne logistique à boucle fermée, qui est une des branches importantes de la chaîne logistique, a reçu une attention particulière au cours des dernières décennies. Toutefois, on trouve peu de recherches dans la littérature sur la chaîne logistique agroalimentaire bien qu’elle soit largement pratiquée dans l’industrie. L'objectif de cette thèse est de proposer de nouveaux modèles et de nouvelles heuristiques pour l’optimisation de la chaîne logistique agroalimentaire à boucle fermée avec emballages réutilisables. A cette fin, trois nouveaux problèmes sont étudiés.Nous étudions d’abord un problème de la chaîne logistique agroalimentaire à boucle fermée avec emballages réutilisables. Ce problème implique un seul fabricant et un seul détaillant. L'externalisation est autorisée. Et le budget d'achat d’emballages réutilisable est limité. L'objectif est de maximiser le profit global de la chaîne logistique. Le problème est formulé en programmation linéaire en nombres mixtes et est démontré NP-difficile. Pour sa résolution, une nouvelle « kernel search-based » heuristique est développée. Les expériences numériques sur un cas d’étude et sur un grand nombre d’instances générées aléatoirement montrent l’efficacité de la méthode proposée.Ensuite, un problème bi-critère de la chaîne logistique agroalimentaire à boucle fermée avec emballages réutilisables est étudié. L'objectif est de maximiser le profit et de minimiser les émissions carbone, simultanément. Dans ce problème, plusieurs détaillants sont considérés. Ce problème est modélisé en programmation linéaire bi-objectif en nombres mixtes et résolu à l’aide d’une méthode de ε-contrainte. En particulier, une heuristique basée sur la « kernel search-based » est développée pour résoudre à chaque itération le problème transformé à un problème monocritère de la méthode de ε-contrainte. Les resultats numériques sur des instances générées aléatoirement indiquent que la performance de la méthode développée est comparable avec celle proposée par le solveur CPLEX.Finalement, nous nous intéressons à un problème intégrant la gestion des stocks et la tournée de véhicules dans la chaîne logistique agroalimentaire à boucle fermée avec emballages réutilisables. Dans ce problème, les emballages réutilisables avec différents niveaux de protection sont considérés. Le problème est formulé en programmation linéaire en nombres mixtes et est démontré NP-difficile. Le modèle proposé est validé via des expériences numériques.

International audience; This paper studies a multi-period, single-manufacturer and single-retailer closed-loop food supply chain with returnable transport items (RTIs) which are used for shipping perishable products. The quality of the products is distinguished according to its age over time. After commodities delivered to the retailer, the emptied returnable transport items are returned to the manufacturer after certain disposes and will be reused in the subsequent shipments. During this process, the manufacturer has to decide when and how many new RTIs to be purchased so as to avoid their shortage and deterioration of products. The objective is to maximize the total expected profit of the supply chain. To cope with the problem, a mixed integer linear programming model is developed and commercial software CPLEX12.6 is applied to solve it. Computational results based on randomly generated instances illustrate the validity and effectiveness of the proposed model.

Background Amorphous silica nanoparticles (SiO2 NPs) have been regarded as relatively benign nanomaterials, however, this widely held opinion has been questioned in recent years by several reports on in vitro and in vivo toxicity. Surface chemistry, more specifically the surface silanol content, has been identified as an important toxicity modulator for SiO2 NPs. Here, quantitative relationships between the silanol content on SiO2 NPs, free radical generation and toxicity have been identified, with the purpose of synthesizing safer-by-design fumed silica nanoparticles. Results Consistent and statistically significant trends were seen between the total silanol content, cell membrane damage, and cell viability, but not with intracellular reactive oxygen species (ROS), in the macrophages RAW264.7. SiO2 NPs with lower total silanol content exhibited larger adverse cellular effects. The SAEC epithelial cell line did not show any sign of toxicity by any of the nanoparticles. Free radical generation and surface reactivity of these nanoparticles were also influenced by the temperature of combustion and total silanol content. Conclusion Surface silanol content plays an important role in cellular toxicity and surface reactivity, although it might not be the sole factor influencing fumed silica NP toxicity. It was demonstrated that synthesis conditions for SiO2 NPs influence the type and quantity of free radicals, oxidative stress, nanoparticle interaction with the biological milieu they come in contact with, and determine the specific mechanisms of toxicity. We demonstrate here that it is possible to produce much less toxic fumed silicas by modulating the synthesis conditions., Particle and Fibre Toxicology, 16 (1), ISSN:1743-8977