Route and fleet design for cyclic inventory routing

Raa, Birger; Dullaert, Wout

doi:10.1016/j.ejor.2016.06.009

Cited by 22 publications

(16 citation statements)

References 17 publications

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“…Other heuristics and metaheuristics for the cyclic IRP have also been presented by Chitsaz et al. (), Raa and Dullaert (), and Zachariadis et al. ().…”

Section: Literature Reviewmentioning

confidence: 97%

A reactive simheuristic using online data for a real‐life inventory routing problem with stochastic demands

Raba

Estrada‐Moreno

Panadero

et al. 2020

Int Trans Operational Res

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In the context of a supply chain for the animal‐feed industry, this paper focuses on optimizing replenishment strategies for silos in multiple farms. Assuming that a supply chain is essentially a value chain, our work aims at narrowing this chasm and putting analytics into practice by identifying and quantifying improvements on specific stages of an animal‐feed supply chain. Motivated by a real‐life case, the paper analyses a rich multi‐period inventory routing problem with homogeneous fleet, stochastic demands, and maximum route length. After describing the problem and reviewing the related literature, we introduce a reactive heuristic, which is then extended into a biased‐randomized simheuristic. Our reactive approach is validated and tested using a series of adapted instances to explore the gap between the solutions it provides and the ones generated by existing nonreactive approaches.

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“…Other heuristics and metaheuristics for the cyclic IRP have also been presented by Chitsaz et al. (), Raa and Dullaert (), and Zachariadis et al. ().…”

Section: Literature Reviewmentioning

confidence: 97%

A reactive simheuristic using online data for a real‐life inventory routing problem with stochastic demands

Raba

Estrada‐Moreno

Panadero

et al. 2020

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

“…Other heuristic and metaheuristic techniques for the cyclic IRP have also been presented by Chitsaz et al. (), Raa and Dullaert (), and Zachariadis et al. ().…”

Section: Literature Reviewmentioning

confidence: 98%

A variable neighborhood search simheuristic for the multiperiod inventory routing problem with stochastic demands

Gruler

Panadero

Armas

et al. 2018

Int Trans Operational Res

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The inventory routing problem (IRP) combines inventory management and delivery route‐planning decisions. This work presents a simheuristic approach that integrates Monte Carlo simulation within a variable neighborhood search (VNS) framework to solve the multiperiod IRP with stochastic customer demands. In this realistic variant of the problem, our goal is to establish the optimal refill policies for each customer–period combination, that is, those individual refill policies that minimize the total expected cost over the periods. This cost is the aggregation of both expected inventory and routing costs. Our simheuristic algorithm allows to consider the inventory changes between periods generated by the realization of the random demands in each period, which have an impact on the quantities to be delivered in the next period and, therefore, on the associated routing plans. A range of computational experiments are carried out in order to illustrate the potential of our simulation–optimization approach.

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“…The vehicles are allowed to perform multiple trips on a single day. Reference [7] proposed a new solution approach for solving CIRP. It builds the solution in two different phases.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulated Annealing for the Multi-Vehicle Cyclic Inventory Routing Problem

Gunawan

Widjaja

et al. 2019

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)

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This paper studies the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) as the extension of the Single-Vehicle CIRP (SV-CIRP). The objective is to minimize both distribution and inventory costs at the customers and to maximize the collected rewards simultaneously. The problem is treated as a single objective optimization problem. A subset of customers is selected for each vehicle including the quantity to be delivered to each customer. For each vehicle, a cyclic distribution plan is developed. We construct a mathematical programming model and propose a simulated annealing (SA) metaheuristic for solving both SV-CIRP and MV-CIRP. For SV-CIRP, experimental results on benchmark instances show that SA is comparable to the state-of-the-art algorithms and it is able to improve 12 best known solutions. For the MV-CIRP, the results show that SA performs better than an Iterated Local Search algorithm.

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Route and fleet design for cyclic inventory routing

Cited by 22 publications

References 17 publications

A reactive simheuristic using online data for a real‐life inventory routing problem with stochastic demands

A reactive simheuristic using online data for a real‐life inventory routing problem with stochastic demands

A variable neighborhood search simheuristic for the multiperiod inventory routing problem with stochastic demands

Simulated Annealing for the Multi-Vehicle Cyclic Inventory Routing Problem

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