Maria João Santos

Abstract
Today, logistics activities are driven by the pressing need to simultaneously increase efficiency, reduce costs, and promote sustainability. In our research, we tackle this challenge by adapting a general vehicle routing problem with deliveries and pickups to accommodate different types of customers. Customers requiring both delivery and pickup services are mandatory, while those needing only a pickup service (backhaul customers) are optional and are only visited if profitable. A mixed-integer linear programming model is formulated to minimize fuel consumption. This model can address various scenarios, such as allowing mandatory customers to be served with combined or separate delivery or pickup visits, and visiting optional customers either during or only after mandatory customer visits. An adaptive large neighborhood search is developed to solve instances adapted from the literature as well as to solve a real-case study of a beverage distributor. The results show the effectiveness of our approach, demonstrating the potential to utilize the available capacity on vehicles returning to the depot to create profitable and environmentally friendly routes, and so enhancing efficient, cost-effective, and sustainable logistics activities. © 2024 International Federation of Operational Research Societies.

Abstract
Food waste poses a significant challenge to the sustainability of traditional food production systems, prompting global efforts to combat waste throughout the supply chain. Sustainable food production emerges as a critical concept in response to increasing concerns about environmental degradation and the need for alternative protein sources driven by global population growth. In this context, insect production offers a promising solution by converting low-value organic waste into nutrient-rich products, thus reducing waste and environmental impact. This paper addresses the urgent need for sustainable and efficient food production systems by introducing a facility location problem within the network design of insect production. The objective is to develop methods to scale insect-derived product production by identifying optimal locations with the best conditions for establishing insect production facilities. Emphasis is placed on connecting suppliers with production, highlighting the critical role suppliers and their by-products play in promoting a sustainable industry. Instances were generated to assess model performance, including supplier and facility locations, by-product availability and selection. Varying by-product availability yielded different optimization outcomes. The experiments results offered insights into the model's behavior under different conditions. The results shown that varying the composition of substrate had a major implication on the augment of costs compared to varying the by-product availability.

Abstract
The Vehicle Routing Problem with Divisible Deliveries and Pickups (VRPDDP) is under-explored in literature, yet it has a wide application in practice in a reverse logistics context, where the collection returnable items must also be ensured along with the traditional delivery of products to customers. problem considers that each customer has both delivery and pickup demands and may be visited twice in the same or different routes (i.e., splitting customers' visits). In several reverse logistics problems, capacity restrictions are required to either allow the movement of the driver inside the vehicle to arrange the loads or to avoid cross-contamination between delivery and pickup loads. In this work, explore the economic and the environmental impacts of the VRPDDP, with and without restrictions the free capacity, and compare it with the traditional Vehicle Routing Problem with Simultaneous Deliveries and Pickups (VRPSDP), on savings achieved by splitting customers visits. An exact method, solved through Gurobi, and an ALNS metaheuristic are coded in Python and used to test well-known and newly generated instances. A multi-objective approach based on the augmented e-constraint method is applied to obtain and compare solutions minimizing costs and CO2 emissions. The results demonstrate that splitting customer visits reduces the CO2 emissions for load-constrained distribution problems. Moreover, savings percentage of the VRPDDP when compared to the VRPSDP is higher for instances with a random network than when a clustered network of customers is considered.

Abstract

Abstract
The Minimum Life on Receipt (MLOR) is a widely used rule that imposes the minimum remaining age a food product must be delivered by the producer to the retailer. In practice, this rule is set by retailers and it is fixed, around 2/3 of the age of products regardless their shelf life. In this work, we study single and two echelon make-to-stock production-inventory problems for fixed-lifetime perishables. Mixed-integer linear optimization models are developed considering the MLOR rule both as decision variable and fixed parameter. When the MLOR rule is a variable, it is considered either a sole decision of the producer or a collaborative decision between retailer and producer. The goal of this work is to compare the supply chain performance considering this innovative setting of optimal MLOR (as a variable) against the traditional setting of fixed MLOR rule. The computational results suggest that allowing flexible MLOR rules according to the shelf life of products and the operational requirements of the producer benefit both entities in the supply chain. In particular, reducing the MLOR requirement in up to 12% does not interfere substantially with the average freshness of products arriving to the retailer, but reduces extensively surplus/waste generation at the producer while keeping a small amount of waste at the retailer.