Internet of Things in urban waste collection

Nowadays, the waste collection management has an important role in urban areas. This paper faces this issue and proposes the application of a metaheuristic for the optimization of a weekly schedule and routing of the waste collection activities in an urban area. Differently to several contributions in literature, fixed periodic routes are not imposed. The results significantly improve the performance of the company involved, both in terms of resources used and costs saving

Vehicle routing and location routing with intermediate stops:A review

This paper reviews the literature on vehicle routing problems and location rout-8 ing problems with intermediate stops. We classify publications into different categories from both an application-based perspective and a methodological perspective. In addition, we analyze the papers with respect to the algorithms and benchmark instances they present. Furthermore, we provide an overview of trends in the literature and identify promising areas for further research.</p

Vehicle routing and location routing with intermediate stops:A review

This paper reviews the literature on vehicle routing problems and location rout-8 ing problems with intermediate stops. We classify publications into different categories from both an application-based perspective and a methodological perspective. In addition, we analyze the papers with respect to the algorithms and benchmark instances they present. Furthermore, we provide an overview of trends in the literature and identify promising areas for further research.</p

Matheuristics: using mathematics for heuristic design

Matheuristics are heuristic algorithms based on mathematical tools such as the ones provided by mathematical programming, that are structurally general enough to be applied to different problems with little adaptations to their abstract structure. The result can be metaheuristic hybrids having components derived from the mathematical model of the problems of interest, but the mathematical techniques themselves can define general heuristic solution frameworks. In this paper, we focus our attention on mathematical programming and its contributions to developing effective heuristics. We briefly describe the mathematical tools available and then some matheuristic approaches, reporting some representative examples from the literature. We also take the opportunity to provide some ideas for possible future development

Formulation and a two-phase matheuristic for the roaming salesman problem: Application to election logistics

In this paper we investigate a novel logistical problem. The goal is to determine daily tours for a traveling salesperson who collects rewards from activities in cities during a fixed campaign period. We refer to this problem as the Roaming Salesman Problem (RSP) motivated by real-world applications including election logistics, touristic trip planning and marketing campaigns. RSP can be characterized as a combination of the traditional Periodic TSP and the Prize-Collecting TSP with static arc costs and time-dependent node rewards. Commercial solvers are capable of solving small-size instances of the RSP to near optimality in a reasonable time. To tackle large-size instances we propose a two-phase matheuristic where the first phase deals with city selection while the second phase focuses on route generation. The latter capitalizes on an integer program to construct an optimal route among selected cities on a given day. The proposed matheuristic decomposes the RSP into as many subproblems as the number of campaign days. Computational results show that our approach provides near-optimal solutions in significantly shorter times compared to commercial solvers

A matheuristic approach combining genetic algorithm and mixed integer linear programming model for production and distribution planning in the supply chain

[EN] A number of research studies has addressed supply chain planning from various perspectives (strategical, tactical, operational) and demonstrated the advantages of integrating both production and distribution planning (PDP). The globalisation of supply chains and the fourth industrial revolution (Industry 4.0) mean that companies must be more agile and resilient to adapt to volatile demand, and to improve their relation with customers and suppliers. Hence the growing interest in coordinating production-distribution processes in supply chains. To deal with the new market¿s requirements and to adapt business processes to industry¿s regulations and changing conditions, more efforts should be made towards new methods that optimise PDP processes. This paper proposes a matheuristic approach for solving the PDP problem. Given the complexity of this problem, combining a genetic algorithm and a mixed integer linear programming model is proposed. The matheuristic algorithm was tested using the Coin-OR Branch & Cut open-source solver. The computational outcomes revealed that the presented matheuristic algorithm may be used to solve real sized problems.This work was supported by the Conselleria de Educación, Investigación, Cultura y Deporte - Generalitat Valenciana for hiring predoctoral research staff with Grant (ACIF/2018/170) and European Social Fund with Grant Operational Program of FSE 2014-2020, the Valencian Community. The research leading to these results received funding from the European Union H2020 Programme with grant agreement No. 958205 "Industrial Data Services for Quality Control in Smart Manufacturing" (i4Q) and the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana entitled "Industrial Production and Logistics Optimization in Industry 4.0" (i4OPT) (Ref. PROMETEO/ 2021/065)Guzmán-Ortiz, BE.; Poler, R.; Andres, B. (2023). A matheuristic approach combining genetic algorithm and mixed integer linear programming model for production and distribution planning in the supply chain. Advances in Production Engineering & Management. 18(1):19-31. https://doi.org/10.14743/apem2023.1.454193118

Integrated planning for electric commercial vehicle fleets:A case study for retail mid-haul logistics networks

Electric commercial vehicles can contribute significantly to sustainable transportation. However, they are still perceived as being less economically viable than internal combustion engine vehicles. To this end, we analyze the deployment of electric commercial vehicles in retail mid-haul logistics fleets for current and future technology scenarios. We develop a novel assessment methodology that combines total cost of ownership calculations with a rich location-routing model. We consider integrated strategic network design and operational routing decisions over a multi-period time horizon, accounting for mixed fleets of electric and conventional vehicles and battery degradation. To solve this problem, we develop a novel matheuristic that embeds a state-of-the-art metaheuristic to take operational routing decisions. With this framework, we analyze a possible transition towards electrified logistics fleets. Starting with a real-world case, we perform sensitivity analyses based on a technology roadmap and further network structures. We discuss cost structures, the time-dependent nature of investment decisions, operational characteristics, and potential emissions savings. We show that in certain cases an electrification of mid-haul logistics fleets is operationally feasible, economically viable, and provides environmental advantages.</p