Abstract

Abstract
This paper deals with multi-objective location-routing problems (MO-LRPs) and follows a sectorizationapproach, which means customers are divided into different sectors, and a distribution centre is opened for eachsector. The literature has considered objectives such as minimizing the number of opened distribution centres,the variances of compactness, distances and demands in sectors. However, the achievement of these objectivescannot guarantee the geographical separation of sectors. In this sense, and as the geographical separation ofsectors can have significant practical relevance, we propose a new objective function and solve a benchmarkof problems with the non-dominated sorting genetic algorithm (NSGA-II), which finds multiple non-dominatedsolutions. A comparison of the results shows the effectiveness of the introduced objective function, since, in thenon-dominated solutions obtained, the sectors are more geographically separated when the values of the objectivefunction improve.

Abstract

Abstract
Additive Manufacturing (AM) is one of the most trending production technologies, with a growing number of companies looking forward to implementing it in their processes. Producing through AM not only means that there are no supplier lead times needed to account for, but also enables production closer to the end customer, reducing then the delivery time. This is especially true for companies with a wide range of low and variable demand products. This paper proposes a mixed integer linear programming (MILP) model for the optimal design of supply chains facing the introduction of AM processes. In the addressed problem, the 3D printers allocation to distribution centers (DC), that will make or customize parts, and the Suppliers-DC-Customers connections for each product need to be defined. The model aims at minimizing the supply chain costs, exploring the trade-offs between safety stock and stockout costs, and between buying and 3D printing a part. The main relevant characteristics of this model are the introduction of stock service levels as decision variables and the use of a linearization of the cumulative distribution function to account for demand uncertainty. A real-world problem from a maintenance provider is solved, showing the applicability of the model. © 2019, IEOM Society International.

Abstract
Logistic decisions involving the location of facilities in connection with vehicle routing appear in many contexts and applications. Given a set of potential distribution centers (DC) and a group of clients, the choice of which DC to open together with the design of a number of vehicle routes, satisfying clients’ demand, may define Location-Routing Problems (LRP). This paper contributes with a new method, the 4-Phase Method (4-PhM), to deal with Capacitated LRP. Relevant advantages of 4-PhM are its generality, the possibilities of handling Multiple-Criteria and of facing large dimension problems. This last aptitude is a consequence of the sectorization phases, which permit a simplification of the solution space. Sectors are constructed by two Simulated Annealing based procedures, and they follow SectorEl, a sectorization approach inspired by electrostatics. In the last phase, the results obtained are evaluated using multicriteria analysis. Here, decision makers play an important role by reflecting preferences in a pairwise comparison matrix of the Analytic Hierarchy Process. Computational results, based on randomly generated instances, confirm the expectations about 4-PhM and its potentiality to deal with LRP. © Springer International Publishing AG 2018.