Mixed integer and heuristics model for the inventory routing problem in fuel delivery

Vidović, Milorad; Popović, Dražen; Ratković, Branislava

doi:10.1016/j.ijpe.2013.04.034

Cited by 77 publications

(39 citation statements)

References 19 publications

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“…(1)- (13). In this study, we propose two heuristic approaches: two-phase method (2PM) and three-phase method (3PM).…”

Section: The Two-phase Methods (2pm)mentioning

confidence: 99%

“…Recently, Vidovic et al [13] also proposed a similar approach to Popovic et al [12], but the way they obtained the initial solution, as well as improving the solution are different. Firstly, they partially solved the MIP model (relaxed MIP model) to obtain the initial solution, and then improving the solution by using a variable neighborhood descent (VND) search.…”

Section: Related Literaturementioning

confidence: 99%

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Optimization Approach for Multi-Period Fuel Replenishment

Charusakwong¹,

Lohatepanont²

2016

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Abstract. This paper proposes mathematical models and solution approaches for solving the multi-period fuel replenishment planning problem. The model aims to search for a set of routes, determining the quantity of several petroleum products to be loaded on individual vehicle compartments, and specifying the quantity to be discharged to customer tanks over a given planning horizon in which multiple constraints are satisfied. The objective function is to minimize the transportation unit cost, equal to the total transportation cost divided by the sum of replenished quantity. As the model size grows exponentially when the number of customers, vehicles, and time period increases, an exact algorithm is not feasible. Hence, in this study, we propose two heuristic approaches: twophase method (2PM) and three-phase method (3PM). The 2PM is primarily designed for solving small problems whereas the 3PM adopts a similar approach but has the ability to solve larger problems. The proposed solutions were tested using a real-life scenario and randomly generated test instance. The results showed that our solution outperforms the solution constructed by experienced planners and also proved that considering multiple periods when devising the fuel replenishment plan, gives superior results in comparison to single periods.

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“…(1)- (13). In this study, we propose two heuristic approaches: two-phase method (2PM) and three-phase method (3PM).…”

Section: The Two-phase Methods (2pm)mentioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

Optimization Approach for Multi-Period Fuel Replenishment

Charusakwong¹,

Lohatepanont²

2016

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“…They can be viewed as Inventory Routing Problems (IRP) with specific additional constraints such as the use of heterogeneous vehicle with compartments, also known as IRP in fuel delivery (see, e.g., Vidović et al, 2014). Malépart et al (2003) propose four heuristics for constructing replenishment plans over a horizon of several working days, where some petrol stations manage their own inventories sending their orders to vendor company whenever they want, and for other stations the inventory is managed by the vendor company who decides the replenishment plans.…”

Section: Literature Reviewmentioning

confidence: 99%

Periodic Capacitated Vehicle Routing for Retail Distribution of Fuel Oils

Carotenuto

Giordani

Massari

et al. 2015

Transportation Research Procedia

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In this paper we consider the final distribution of fuel oil from a storage depot to a set of petrol stations faced by an oil company, which has to decide the weekly replenishment plan for each station, and determine petrol station visiting sequences (vehicle routes) for each day of the week, assuming a fleet of homogeneous vehicles (tankers). The aim is to minimize the total distance travelled by tankers during the week, while loading tankers possibly near to their capacity in order to maximize the resource utilization. The problem is modelled as a generalization of the Periodic Vehicle Routing Problem (PVRP). Due to the large size of the real instances which the company has to deal with, we solve the problem heuristically. We propose a hybrid genetic algorithm that successfully address the problem inspired to a known hybrid genetic algorithm from the literature for the PVRP. However, the proposed algorithm adopts some techniques and features tailored for the particular fuel oil distribution problem, and it is specifically designed to deal with real instances derived from the fuel oil distribution in the European context that are profoundly different from the PVRP instances available from literature. The proposed algorithm is evaluated on a set of real case studies and on a set of randomly generated instances that hold the same characteristics of the former.

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“…Adelman [23], Hvattum and Lokketangen [24], Hvattum et al [25], and Mete and Zabinsky [26] studied the stochastic version of the problem. A survey on IRP is presented by Vidovic et al [27]. Other papers in the literature integrate inventory, lot-sizing, and vehicle routing decisions such as Nananukul [28]; the author developed a reactive Tabu search procedure for solving a production-distribution supply chain and improved results using a path relinking strategy; Cetinkaya et al [29] studied an integrated multiproduct inventory lotsizing and vehicle routing problem and presented an iterative solution approach in which the problem is decomposed into inventory and routing subproblems; Chen and Sarker [30] established an integrated optimal model of inventory lotsizing vehicle routing of multisupplier single-manufacturer 2 Mathematical Problems in Engineering with milk-run JIT delivery and solved it using an ant colony optimization algorithm; and Kechmane et al [31] proposed a mathematical model to optimize transport cost and delivery lot-sizing in a single level logistic network and solved it using a MILP solver.…”

Section: Introductionmentioning

confidence: 99%

Optimization of a Two-Echelon Location Lot-Sizing Routing Problem with Deterministic Demand

Kechmane

Nsiri²,

Baalal

2018

Mathematical Problems in Engineering

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This paper aims to solve a multiperiod location lot-sizing routing problem with deterministic demand in a two-echelon network composed of a single factory, a set of potential depots, and a set of customers. Solving this problem involves making strategic decisions such as location of depots as well as operational and tactical decisions which include customers' assignment to the open depots, vehicle routing organization, and inventory management. A mathematical model is presented to describe the problem and a genetic algorithm combined with a local search procedure is proposed to solve it and is tested over three sets of instances.

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Mixed integer and heuristics model for the inventory routing problem in fuel delivery

Cited by 77 publications

References 19 publications

Optimization Approach for Multi-Period Fuel Replenishment

Optimization Approach for Multi-Period Fuel Replenishment

Periodic Capacitated Vehicle Routing for Retail Distribution of Fuel Oils

Optimization of a Two-Echelon Location Lot-Sizing Routing Problem with Deterministic Demand

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