Comparing techniques for modelling uncertainty in a maritime inventory routing problem

Rodrigues, Filipe; Agra, Agostinho; Christiansen, Marielle; Hvattum, Lars Magnus; Requejo, Cristina

doi:10.1016/j.ejor.2019.03.015

Cited by 35 publications

(23 citation statements)

References 21 publications

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“…Travel time uncertainty of services in a global intermodal network may lead to infeasible transshipments in addition to the commonly studied outcome of late or early delivery at destinations [9,14]. An illustrative example is shown in Fig.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…Here, M is a large enough number which ensures the time compatibility between shipment r and service s when binary variable x rs equals to 1, but leaves the constraints "open" if x rs is 0. Constraints (13)(14)(15)(16) ensure that the arrival time of service s ∈ S − i plus loading and unloading time must be earlier than the departure time of service q ∈ S + i if request r will be transported by service s entering terminal i and by service q leaving terminal i.…”

Section: Mathematical Formulationmentioning

confidence: 99%

See 1 more Smart Citation

A Global Intermodal Shipment Matching Problem Under Travel Time Uncertainty

Guo

Atasoy

Blokland

et al. 2020

Lecture Notes in Computer Science

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Global intermodal transportation involves the movement of shipments between inland terminals located in different continents by using ships, barges, trains, trucks, or any combination among them through integrated planning at a network level. One of the challenges faced by global operators is the matching of shipment requests with transport services in an integrated global network. The characteristics of the global intermodal shipment matching problem include acceptance and matching decisions, soft time windows, capacitated services, and transshipments between multimodal services. The objective of the problem is to maximize the total profits which consist of revenues, travel costs, transfer costs, storage costs, delay costs, and carbon tax. Travel time uncertainty has significant effects on the feasibility and profitability of matching plans. However, travel time uncertainty has not been considered in global intermodal transport yet leading to significant delays and infeasible transshipments. To fill in this gap, this paper proposes a chance-constrained programming model in which travel times are assumed stochastic. We conduct numerical experiments to validate the performance of the stochastic model in comparison to a deterministic model and a robust model. The experiment results show that the stochastic model outperforms the benchmarks in total profits.

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Section: Problem Descriptionmentioning

confidence: 99%

Section: Mathematical Formulationmentioning

confidence: 99%

A Global Intermodal Shipment Matching Problem Under Travel Time Uncertainty

Guo

Atasoy

Blokland

et al. 2020

Lecture Notes in Computer Science

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“…We assume that the demand in one period can either be met in that period (using production of that period or using stocks from production in previous periods), or satisfied with delay in a later period. The demand satisfied with delay in a given time period is referred to as the backlog (Rodrigues et al 2019). Consider for each time period t ∈ N , the unit holding cost h t , the unit backlog cost b t , and the unit production cost c t .…”

Section: The Stochastic Lot-sizing Problem With Setupsmentioning

confidence: 99%

Weighted proximity search

et al. 2021

Self Cite

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Proximity search is an iterative method to solve complex mathematical programming problems. At each iteration, the objective function of the problem at hand is replaced by the Hamming distance function to a given solution, and a cutoff constraint is added to impose that any new obtained solution improves the objective function value. A mixed integer programming solver is used to find a feasible solution to this modified problem, yielding an improved solution to the original problem. This paper introduces the concept of weighted Hamming distance that allows to design a new method called weighted proximity search. In this new distance function, low weights are associated with the variables whose value in the current solution is promising to change in order to find an improved solution, while high weights are assigned to variables that are expected to remain unchanged. The weights help to distinguish between alternative solutions in the neighborhood of the current solution, and provide guidance to the solver when trying to locate an improved solution. Several strategies to determine weights are presented, including both static and dynamic strategies. The proposed weighted proximity search is compared with the classic proximity search on instances from three optimization problems: the p-median problem, the set covering problem, and the stochastic lot-sizing problem. The obtained results show that a suitable choice of weights allows the weighted proximity search to obtain better solutions, for 75$$\%$$ % of the cases, than the ones obtained by using proximity search and for 96$$\%$$ % of the cases the solutions are better than the ones obtained by running a commercial solver with a time limit.

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“…Meanwhile, the empty container inventory of the visited ports can be controlled within a reasonable range. Rodrigues et al [31] studied a kind of maritime inventory route problem under the circumstance of uncertain sailing time considering the possible delay during the voyage, which is a crucial mode to avoid inventory excess or shortage of empty containers at port yards. At the same time, the methods to deal with uncertainty intensively, such as deterministic model with stock buffer, robust optimization and stochastic programming are also considered.…”

Section: Introductionmentioning

confidence: 99%

Optimization on the Multi-period Empty Container Repositioning Problem in Regional Port Cluster Based upon Inventory Control Strategies

Cai¹,

Li²,

Yin³

et al. 2021

Preprint

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Within the area of regional port clusters, this paper establishes a multi-period mixed integer programming model to optimize the empty container repositioning between public hinterlands and ports, comprehensively considering the quantitative and periodic inventory control strategy. By using Markov decision process combined with dynamic programming method, this paper dynamically optimizes the empty container inventory threshold (D;U) under quantitative strategy and S under periodical strategy at each port within the regional port clusters. On this basis, this paper optimizes the empty container repositioning scheme between public hinterlands and ports. Meanwhile, Liaoning coastal regional port cluster and its northeast hinterland are selected as the objects to solve this model and the results show that the total cost of shipping company can be saved by 14.16% and 11.92% respec- tively by the quantitative and periodical inventory control strategy. Selecting the quantity of public hinterland terminals, the empty container demand of public hinterland terminals and ports, the inventory threshold of empty containers and other factors, this paper carries on the sensitivity analysis. This paper validates inventory control strategy can weaken the shipping company in the influence of the external environment changes. And the quantitativeinventory control strategy can reduce the total cost value to a greater extent and more effective in cost control than periodical strategy.

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Comparing techniques for modelling uncertainty in a maritime inventory routing problem

Cited by 35 publications

References 21 publications

A Global Intermodal Shipment Matching Problem Under Travel Time Uncertainty

A Global Intermodal Shipment Matching Problem Under Travel Time Uncertainty

Weighted proximity search

Optimization on the Multi-period Empty Container Repositioning Problem in Regional Port Cluster Based upon Inventory Control Strategies

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