A Hybrid Heuristic based on Iterated Local Search for Multivehicle Inventory Routing Problem

Santos, Edcarllos; Ochi, Luiz Satoru; Simonetti, Luidi; González, Pedro Henrique

doi:10.1016/j.endm.2016.03.026

Cited by 19 publications

(13 citation statements)

References 4 publications

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“…The multi‐product and multi‐vehicle IRP is studied in Coelho and Laporte [41,42] and Cordeau et al [44]. More recently, metaheuristics algorithms were proposed in Santos et al [91] and Alvarez et al [6]. The former proposed a hybrid multi‐start algorithm based on an iterated local search, while the latter developed an iterated local search and a simulated annealing algorithm.…”

Section: Inventory Routing Problems In the E‐commerce Eramentioning

confidence: 99%

Recent challenges in Routing and Inventory Routing: E‐commerce and last‐mile delivery

Archetti

Bertazzi

2020

Networks

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In the e‐commerce era, vendors have to satisfy a large number of on‐line orders, mainly from private customers, with low weight and volume, reduced delivery time, and overlap of customers' time windows. Production is made available all day long. New strategies and new technologies are emerging for deliveries. The processing time of the orders is reduced. These new features generate interesting challenges in formulating and solving Routing and Inventory Routing problems. After discussing these features and the corresponding challenges, we recall the relevant literature in Routing and Inventory Routing and provide future research directions, mainly related to routing problems with release dates, routing problems with crowdshipping, and inventory routing problems in the e‐commerce era.

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Section: Inventory Routing Problems In the E‐commerce Eramentioning

confidence: 99%

Recent challenges in Routing and Inventory Routing: E‐commerce and last‐mile delivery

Archetti

Bertazzi

2020

Networks

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“…Permasalahan IRP juga dikembangkan oleh (Chitsaz, Divsalar, and Vansteenwegen 2016) untuk pola distribusi cyclic, selanjutnya disebut model Cyclical Inventory Routing Problem (CIRP). Permasalahan IRP dengan multi vehicle diperkenalkan oleh (Santos, Satoru, and Simonetti 2016) dan (Soysal 2016 (…”

Section: Pendahuluanunclassified

Optimasi Pendistribusian Produk Menggunakan Model Fuzzy Multiobjektif Cyclical Inventory Routing Problem

Susanti¹,

Indrawati²,

Sitepu³

et al. 2020

MTK

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In distribution activities, travel time is influenced by several factors, such as vehicle conditions, traffic conditions and road conditions. Uncertain traffic conditions cause the travel time can not be defined with certainty (uncertain). If several variables are in a uncertain condition then a deterministic approach is not appropriate. Fuzzy approach, can be used to overcome uncertainty conditions. In this study, the optimal route for chicken egg delivery using the fuzzy Multiobjective Cyclical Inventory Routing Problem (FMOCIRP) model with time and cost is expressed by triangular fuzzy numbers. Model completion using Winqsb software. An optimal shipping route is obtained with a total cost of Rp 114,000 and a total delivery time of 132 minutes. The first optimal delivery route is distributor, retailer 1, retailer 2, retailer 3 and back to the distributor. The second route is distributor, retailer 5, retailer 4 and back to the distributor.

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“…Santos et al. () also proposed an ILS‐based hybrid method for the IRP, with similar local search and perturbation algorithms. Different to their approach, the ILS proposed in this paper applies the local search heuristic in a multistart approach to explore more intensively and effectively the search space.…”

Section: Metaheuristic Algorithmsmentioning

confidence: 99%

“…These instances were originally created for the single‐vehicle IRP, but they have also been used for the multivehicle IRP (Archetti et al., ; Coelho and Laporte, ; Desaulniers et al., ; Santos et al., ). Following the common practice in the literature, we use two to five vehicles in addition to the single‐vehicle case, resulting in 800 instances.…”

Section: Computational Experimentsmentioning

confidence: 99%

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Iterated local search and simulated annealing algorithms for the inventory routing problem

Álvarez

Munari

Morábito

2018

Int Trans Operational Res

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This paper addresses the inventory routing problem (IRP), which consists in defining the customer visit schedule, the delivery quantities, and the vehicle routing plan to meet the demands of a set of customers over a given time horizon. We consider the variant with a single item, a single supplier, multiple vehicles, and a finite multiperiod planning horizon, minimizing the sum of inventory and travel costs. In addition, we address an alternative objective function that minimizes the logistic ratio, defined as the total travel cost divided by the total quantity delivered to customers. This second objective function, while more realistic in some logistics settings, poses a challenge for integer programming models and exact methods because of its nonlinearity. To our knowledge, no heuristic method has been proposed to address this objective in the IRP variant addressed in this paper. To solve this problem with each of these objective functions, we propose effective metaheuristic algorithms based on iterated local search and simulated annealing. Computational experiments show that these algorithms provide reasonably high-quality solutions in relatively short running times for both objective functions when compared to other methods for well-known instances from the literature. Moreover, the algorithms produce new best solutions for some of these instances.

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A Hybrid Heuristic based on Iterated Local Search for Multivehicle Inventory Routing Problem

Cited by 19 publications

References 4 publications

Recent challenges in Routing and Inventory Routing: E‐commerce and last‐mile delivery

Recent challenges in Routing and Inventory Routing: E‐commerce and last‐mile delivery

Optimasi Pendistribusian Produk Menggunakan Model Fuzzy Multiobjektif Cyclical Inventory Routing Problem

Iterated local search and simulated annealing algorithms for the inventory routing problem

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