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During the past few years, transportation of agricultural products is increasingly becoming a crucial problem in supply chain logistics. In this paper, we present a new mathematical formulation and two solution approaches for an intermodal transportation problem. The proposed bi-objective model is applied to the transportation of agricultural products from Morocco to Europe to minimise both the transportation cost either in the form of uni-modal or intermodal, as well as the maximal overtime to delivery products. The first solution approach is based on a non-dominated sorting genetic algorithm improved by a local search heuristic and the second one is the GRASP algorithm (Greedy Randomised Adaptive Search Procedure) with iterated local search heuristics. They are tested on theoretical and real case benchmark instances and compared with the standard NSGA-II. Results are analysed and the efficiency of algorithms is discussed using some performance metrics.

The rapid increase in urbanization results in an increase in the volume of municipal solid waste produced every day, causing overflow of the garbage cans and thus distorting the city’s appearance; for this and environmental reasons, smart cities involve the use of modern technologies for intelligent and efficient waste management. Smart bins in urban environments contain sensors that measure the status of containers in real-time and trigger wireless alarms if the container reaches a predetermined threshold, and then communicate the information to the operations center, which then sends vehicles to collect the waste from the selected stations in order to collect a significant waste amount and reduce transportation costs. In this article, we will address the issue of the Dynamic Multi-Compartmental Vehicle Routing Problem (DM-CVRP) for selective and intelligent waste collection. This problem is summarized as a linear mathematical programming model to define optimal dynamic routes to minimize the total cost, which are the transportation costs and the penalty costs caused by exceeding the bin capacity. The hybridized genetic algorithm (GA) is proposed to solve this problem, and the effectiveness of the proposed approach is verified by extensive numerical experiments on instances given by Valorsul, with some modifications to adapt these data to our problem. Then we were able to ensure the effectiveness of our approach based on the results in the static and dynamic cases, which are very encouraging.

Dynamic wireless charging (DWC) facilitates the travel of electric vehicles (EVs) on highways because it can charge EVs without contact and it does not have a recharging time as it can charge vehicles in motion by a set of power transmitters on the road. This work considers a highway road with DWC and a fleet of electric vehicles with heterogeneous batteries to begin a trip from the origin of the highway noted by O to the destination noted by S. As the usage of DWC is not free, this study seeks to install entry gates to the DWC if the vehicles need to charge their batteries and exit gates to the main road if the vehicles wish to stop the recharge. For this purpose, the first objective is to minimize the usage cost paid by each vehicle type to use the DWC during the trip on the highway. The second objective is to find the lower installation cost of the gates on the road. This work proposes to model the problem as a mathematical problem and validate it with the CPLEX optimizer using limited instances and, finally, solves the problem using the non-dominated sorting genetic algorithm (NSGA-II).