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In this chapter, four bi-objective vehicle routing problems are considered. Weighted-sum approach optimization models are formulated with the use of mixed-integer programming. In presented optimization models, maximization of capacity of truck versus minimization of utilization of fuel, carbon emission, and production of noise are taken into account. The problems deal with real data for green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country, and La Rioja, Spain.

Heterogeneous fleet of trucks is considered. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Modern logistic companies planning delivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, and utilization of fuel, carbon emission, and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution. The computational experiments were performed using the AMPL programming language and the CPLEX solver.

The purpose of this chapter is to optimize multi-criteria formulation for green vehicle routing problems by mixed integer programming. This research is about the road freight transportation of a Spanish company of groceries. This company has more power in the north of Spain and hence it was founded there. The data used for the computational experiments are focused in the northern region of Spain. The data have been used to decide the best route in order to obtain a minimization of costs for the company. The problem focused on the distance traveled and the altitude difference; by studying these parameters, the best solution of route transportation has been made. The software used to solve this model is CPLEX solver with AMPL programming language. This has been helpful to obtain the results for the research and some conclusions have been obtained from them.

The purpose of this chapter is to solve multi-objective formulation for traveling salesman and transportation problems. Computations are based on real data for the road freight transportation of a Spanish company. The company was selected because of its importance in Spanish economy and market. This company is important in the whole country; however, it has its higher importance in the northern part of Spain. The requirements for these models are the minimization of total distance and the CO₂ emissions. To achieve this, it is required to know and carry out the minimization of the total distance traveled by the trucks during the deliveries. The deliveries are going to be executed between the different locations, nodes, in the region, and Elorrio, where the depot is situated. The data have been used to decide the best route in order to obtain a minimization of cost for the company. As it was mentioned earlier, the problems are focused on the reduction of the amount of CO₂ emissions and minimization of total distance; by studying different parameters, the best solutions of route transportation have been obtained. The software used to solve these models is CPLEX solver with AMPL programming language.

The last decades have witnessed an increased interest in urban logistics originating from both the research and the practitioners’ communities. Sustainable freight transports today are on the political, social and technological agenda of many actors operating in urban contexts. Due to the extent of the covered areas and the continuous progress in many fields, the resulting body of research on urban logistics appears quite fragmented. From an engineering management perspective, the purpose of this paper is to present a systematic literature review (SLR) that aims to consolidate the knowledge on urban logistics, analyse the development of the discipline, and provide future research directions.

The paper discusses the main evidence emerging from a SLR on urban logistics. The corpus resulting from the SLR has been used to perform a citation network analysis and a main path analysis that together underpin the identification of the most investigated topics and methodologies in the field.

Through the analysis of a corpus of 104 articles, the most important research contributions on urban logistics that represent the structural backbone in the development of the research over time in the field are detected. Based on these findings, this work identifies and discusses three areas of potential interest for future research.

This paper presents an SLR related to a research area in which the literature is extremely fragmented. The results provide insights about the research path, current trends and future research directions in the field of urban logistics.

The purpose of this paper is to present a problem-based learning (PBL) activity that uses a decision support system (DSS) to teach one of the most fundamental topics in distribution planning: vehicle routing.

The authors describe their teaching experience in a logistics and supply chain management (LSCM) course. In the PBL activity proposed, students need to solve a typical vehicle routing case with no previous theoretical background taught. The paper is written as a teaching guide for other instructors, detailing how the activity may be carried out in class.

The PBL activity involved students from the very beginning, challenging them to solve a rather complicated problem. Its acceptance was very positive according to the student feedback survey conducted after the activity. Only when struggling with the difficulties of the case proposed, did students really appreciate the potential value of a DSS for making better decisions. Moreover, this activity raised concerns about how DSSs must be adapted for implementation in every business scenario.

Teaching logistics management goes beyond lecturing on elemental concepts and tools; it is also about applying this knowledge to manage things. Although several PBL initiatives have been reported to be successful in the field of LSCM, this one incorporates a web-based DSS. The main issue in PBL activities is finding authentic and representative problems to develop transferable skills, and currently most logistics problems are solved using DSS.