Hybrid heuristic for the inventory location-routing problem with deterministic demand

Guerrero, William J.; Prodhon, Caroline; Velasco, Nubia; Amaya, Ciro Alberto

doi:10.1016/j.ijpe.2013.07.025

Cited by 95 publications

(56 citation statements)

References 24 publications

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“…Produk yang dikaji oleh Sajjadi et al [6] terdiri dari multi produk dan permintaannya bersifat deterministik. Selain itu, terdapat pula model yang dikembangkan oleh Guerrero et al [7] yang mengembangkan model integrasi keputusan lokasi, perutean kendaraan, dan kebijakan persediaan yang terdiri dari sebuah pabrik, multi depot, dan multi ritel. Sama halnya dengan Ambrosino dan Scutella [4], pada dasarnya Guerrero et al [7] juga tidak mempertimbangkan persediaan, tetapi hanya mempertimbangkan aliran barang dari satu entitas ke entitas lain.…”

Section: Pendahuluanunclassified

“…Selain itu, terdapat pula model yang dikembangkan oleh Guerrero et al [7] yang mengembangkan model integrasi keputusan lokasi, perutean kendaraan, dan kebijakan persediaan yang terdiri dari sebuah pabrik, multi depot, dan multi ritel. Sama halnya dengan Ambrosino dan Scutella [4], pada dasarnya Guerrero et al [7] juga tidak mempertimbangkan persediaan, tetapi hanya mempertimbangkan aliran barang dari satu entitas ke entitas lain. Pembahasan secara lengkap mengenai penelitianpenelitian yang telah mengembangkan model integrasi keputusan lokasi, perutean kendaraan, dan kebijakan persediaan dapat dilihat pada Saragih et al [8].…”

Section: Pendahuluanunclassified

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Model Integrasi Keputusan Lokasi, Perutean Kendaraan, dan Pengendalian Persediaan Pada Sistem Rantai Pasok Tiga Eselon

Saragih¹,

Bahagia²,

Suprayogi³

et al. 2017

jti

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This research develops an integration model that simultaneously optimizes location, routing, and inventory decisions in a three-echelon supply chain system that has never been developed before. Location, routing, and inventory decisions are related to one another. For example, delivery in small quantity and often frequency decreases inventory cost but increases transportation cost. Furthermore, routing and inventory decisions affect location decision for it is determined based on minimum system cost criteria. Failure to involve inventory cost and transportation cost into consideration when determine location decision can cause suboptimality. Therefore, how to determine location, routing, and inventory decisions optimally become important issues in design a logistics system. Entities involved in this research are a supplier, multi depots, and multi retailers. Demand of retailers is probabilistic and follows a normal distribution. Number of product considered is single product. The developed integration model is then solved with optimal method and heuristic method. After being compared with decomposition model, it is concluded that the integration model results smaller total cost of system. Keywords:Integration, inventory control, location decision, multi echelon, vehicle routing. PendahuluanKeputusan lokasi, pengendalian persediaan, dan perutean kendaraan merupakan keputusan yang saling terkait satu dengan yang lain (Liu dan Lin [1]). Keputusan pengendalian persediaan, seperti ukuran lot pemesanan dan frekuensi pemesanan akan mempengaruhi baik itu ongkos persediaan dan ongkos transportasi. Sebagai contoh, pengiriman dalam kuantitas yang sedikit dan frekuensi yang sering menyebabkan pengurangan ongkos persediaan tetapi membutuhkan tambahan ongkos transportasi (Liu dan Lee [2]

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Section: Pendahuluanunclassified

Model Integrasi Keputusan Lokasi, Perutean Kendaraan, dan Pengendalian Persediaan Pada Sistem Rantai Pasok Tiga Eselon

Saragih¹,

Bahagia²,

Suprayogi³

et al. 2017

jti

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“…One can find LRP variants with, for instance, bounds on the number of open depots (Laporte, Nobert, and Arpin 1986;Laporte and Nobert 1981), uncapacitated depots (Burke and Tuzun 1999), mobile depots (Del Pia and Filippi 2006;Amaya, Langevin, and Trépanier 2007); with a heterogeneous fleet (Ambrosino and Scutellà 2001); with bounds on the route length (Laporte and Nobert 1981;Berger, Coullard, and Daskin 2007), or constraints on both route length and customer deadline (Aksen and Altinkemer 2008); variants arising from the study of emergency situations (Rath and Gutjahr 2014); variants with the possibility of roundtrip and multitrip routes (Lin, Chow, and Chen 2002), open routes (Berger 1997) or delivery and pickup routes (Nagy and Salhi 1998;Karaoglan et al 2012); more complex variants with multiperiod planning (Prodhon and Prins 2008) or inventory management (Liu and Lee 2003;Guerrero et al 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

The Multicommodity-Ring Location Routing Problem

Gianessi

Alfandari

Létocart

et al. 2016

Transportation Science

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T he multicommodity-ring location routing problem (MRLRP) studied in this paper is an NP-hard minimization problem arising in city logistics. The aim is to locate a set of urban distribution centers (UDCs) and to connect them via a ring in which massive flows of goods will circulate. Goods are transported from gates located outside the city to a UDC, and either join a second UDC through the ring before being delivered in electric vans to the final customers or are delivered directly to the customers from the first UDC. The reverse trip with pickup and transportation to the gates is also possible. A delivery service path starts at a particular UDC, then visits a subset of customers and ends at the same UDC, another UDC, or a self-service parking lot (SPL). A pickup route can start from an SPL or a UDC and ends at a UDC. The objective is to minimize the sum of the installation costs of the ring, flow transportation costs, and routing costs. The MRLRP belongs to the class of location-routing problems (LRP). We model it with a set-partitioning-like representation of delivery and pickup trips and arc-flow elements to describe goods transportation in the ring and between the ring and the gates. We present three approaches to solving the MRLRP: an exact method for small-size instances, a matheuristic for instances of a larger size, and a hybrid approach that applies the exact method to the columns output by the matheuristic. Numerical results are provided for an exhaustive set of instances, obtained by extending benchmark instances of the capacitated LRP with additional MRLRP features.

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“…Guerrero et al [39] proposed an algorithm for multiperiod LIRP with deterministic demand in a three-layer supply chain composed of a single supplier, potential depots, and customers; a hybrid heuristic and exact solution method are developed to solve the problem as well as an intensification phase to investigate the inventory and routing decision where the location and customers assignments are fixed and a dynamic lot-sizing problem is solved using a MIP solver. Nekooghadirli et al [40] studied a biobjective locationrouting-inventory model with multiperiod, multiproduct, stochastic demand and probabilistic travelling time among customers; their model aims to minimize the total cost and maximize the average time for delivering commodities to customers; and Zhang et al [41] presented a hybrid metaheuristic combined with simulated annealing method to solve a LIRP in a two-echelon network composed of multiple capacitated depots and final customers.…”

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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Hybrid heuristic for the inventory location-routing problem with deterministic demand

Cited by 95 publications

References 24 publications

Model Integrasi Keputusan Lokasi, Perutean Kendaraan, dan Pengendalian Persediaan Pada Sistem Rantai Pasok Tiga Eselon

Model Integrasi Keputusan Lokasi, Perutean Kendaraan, dan Pengendalian Persediaan Pada Sistem Rantai Pasok Tiga Eselon

The Multicommodity-Ring Location Routing Problem

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

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