The Consistent Vehicle Routing Problem with heterogeneous fleet

Stavropoulou, Foteini

doi:10.1016/j.cor.2021.105644

Cited by 18 publications

(8 citation statements)

References 58 publications

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“…Complex models consider constraints like delivery windows and vehicle types, generating various VRP problems. Heterogeneous fleet VRP (HVRP) 57 involves multiple vehicle types with different capacities. Time-dependent VRP (TDVRP) 58 incorporates time windows for deliveries, penalizing delays.…”

Section: Tsp Vrpmentioning

confidence: 99%

Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery

Malashin,

Tynchenko,

Masich

et al. 2024

Preprint

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This study explores groupage delivery optimization through a two-stage GA framework. The goal of optimization is to define locations of regional branch warehouses of Logistics Network to reduce transportation costs. The first stage of the GA focuses on identifying branch warehouses from a list of cities and uses the standard binary string approach, while the second stage solves Vehicle Routing Problem (VRP) using combinatorial GA. This research contributes to advancing logistics optimization methodologies and provides valuable insights for solving Location Routing Problem (LRP) which entails two problems: the Facility Location Problem (FLP) and the Multiple Vehicle Routing Problem (MVRP).

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Section: Tsp Vrpmentioning

confidence: 99%

Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery

Malashin,

Tynchenko,

Masich

et al. 2024

Preprint

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“…Seiring dengan perkembangan yang ada, jenis dan metode penyelesaian VRP sangat beragam. Stavropoulou [4], menyelesaikan consistent vehicle routing problem dengan armada heterogen. Penelitian tersebut menggunakan metode heuristik untuk penyelesaiannya dan membuat beberapa skenario untuk melihat peningkatan biaya yang mungkin.…”

Section: Pendahuluanunclassified

Perancangan Rute Distribusi Air Minum Dalam Kemasan dengan Capacitated Vehicle Routing Problem

Mafaza,

Muslim

2023

MATRIK

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Perusahaan distributor Air Minum Dalam Kemasan (AMDK) yang berlokasi di Semarang memiliki dua kendaraan untuk melakukan distribusi ke 16 lokasi distribusi di dalam Semarang. Permasalahan yang dihadapi yaitu perusahaan melakukan distribusi tanpa memperhitungkan jarak tempuh, kuantitas permintaan yang berbeda-beda di setiap lokasi, keterbatasan jumlah dan kapasitas kendaraan, serta lokasi pelanggan yang tersebar di Semarang. Penelitian perlu dilakukan dengan menggunakan Capacitated Vehicle Routing Problem (CVRP) untuk mendapatkan rute distribusi dengan jarak dan waktu tempuh distribusi optimal. Penelitian ini menggunakan pendekatan Mixed Integer Linear Programming (MILP) dengan metode Branch and Bound. Model matematika dibuat dan diterjemahkan ke dalam bahasa pemrograman LINGO untuk dijalankan dan menghasilkan rute optimal. Hasil pada penelitian ini yaitu didapatkan dua rute optimal untuk setiap kendaraan 1 dan 2 melakukan distribusi AMDK ke 16 lokasi. Jumlah muatan juga didapatkan untuk masing-masing rute dengan tidak melebihi kapasitas kendaraan. Total jarak yang ditempuh berkurang sebesar 28% dan dapat menghemat total waktu tempuh sebesar 11%. Analisis sensitivitas dilakukan dengan mengubah parameter permintaan dan hasilnya yaitu terjadi penambahan rute menjadi 3 rute ketika kondisi kenaikan permintaan sebesar 5%, 10%, dan 15% serta terdapat pengaruh perubahan pada rute, jarak, dan waktu tempuh ketika kondisi penurunan permintaan 15% serta kondisi kenaikan permintaan 5%, 10%, dan 15%.

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“…Maxino et al ( 2022) [14] presented an Adaptive Iterated Local Search (AILS) heuristic for the HFVRP. Experiments confirmed that the AILS outperformed other leading metaheuristics usually and suggested further application of this approach to larger HVRP instances.…”

Section: Vehicle Routing Problemmentioning

confidence: 99%

The Novel Strategy of Differential Evolution for Multi-Fleet Size and Vehicle Routing Problem in Logistics Service Providers

Worasan,

Moonsri,

Saenchaiyathon

2023

E3S Web Conf.

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This paper focuses on determining routes for logistics service providers from distribution centers to customers with the objective of minimizing the total costs. Despite being a particular example of the vehicle routing problem (VRP), this issue is more complicated than the basic VRP, especially since each vehicle contains heterogeneous capacity. This paper presents the novel strategy of Differential Evolution (NSDE) to solve multi-fleet size and Vehicle Routing Problems in logistics service providers (MFSVRP-LSP). Our work aims to minimize distance. The validation of NSDE (i.e., DE, NSDE1, NSDE2, NSDE3, NSDE4) was conducted by the comparison of the current practice. The relative improvement (RI) between the standard DE and the NSDE1, NSDE2, NSDE3, and NSDE4 in the MFSVRP-LSP. The NSDE4 outperformed the standard DE follow by my report. Furthermore, our suggested technique can be used for similar logistics in Thailand.

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The Consistent Vehicle Routing Problem with heterogeneous fleet

Cited by 18 publications

References 58 publications

Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery

Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery

Perancangan Rute Distribusi Air Minum Dalam Kemasan dengan Capacitated Vehicle Routing Problem

The Novel Strategy of Differential Evolution for Multi-Fleet Size and Vehicle Routing Problem in Logistics Service Providers

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