In the Multi-Period Petrol Station Replenishment Problem (MPSRP) the aim is to optimize the delivery of several petroleum products to a set of petrol stations over a given planning horizon. One must determine, for each day of the planning horizon, how much of each product should be delivered to each station, how to load these products into vehicle compartments, and how to plan vehicle routes. The objective is to maximize the total profit equal to the revenue, minus the sum of routing costs and of regular and overtime costs. This article describes a heuristic for the MPSRP. It contains a route construction and truck loading procedures, a route packing procedure, and two procedures enabling the anticipation or the postponement of deliveries. The heuristic was extensively tested on randomly generated data and compared to a previously published algorithm. Computational results confirm the efficiency of the proposed methodology.

In the Petrol Station Replenishment Problem with Time Windows (PSRPTW) the aim is to optimize the delivery of several petroleum products to a set of petrol stations using a limited heterogeneous fleet of tank-trucks. More specifically, one must determine the quantity of each product to deliver, the assignment of products to truck compartments, delivery routes, and schedules. The objective is to maximize the total profit equal to the sales revenue, minus the sum of routing costs and of regular and overtime costs. This article first proposes a mathematical formulation of the PSRPTW. It then describes two heuristics based on arc preselection and on route preselection. Extensive computational tests confirm the efficiency of the proposed heuristics.

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This paper considers a generalized version of the trip packing problem that we encountered as a sub-problem of the petrol stations replenishment problem. In this version we have to assign a number of trips to a fleet composed of a limited number of non-identical tank-trucks. Each trip has a specific duration, working time of vehicles is limited and the net revenue of each trip depends on the truck used. The paper provides a mathematical formulation of the problem and proposes some construction, improvement and neighbourhood search solution heuristics. A set of benchmark problem instances is created in a way that reflects real-life situations and used to analyse the performance of the proposed heuristics. A reallife case is also used to further assess the proposed heuristics.