A robust hybrid heuristic algorithm to solve multi-plant milk-run pickup problem with uncertain demand in automobile parts industry

Wu, Qian; Wang, X.; He, Yongle; Xuan, Jifeng; He, Wei

doi:10.14743/apem2018.2.282

Cited by 11 publications

(6 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Metode optimasi dapat diterapkan untuk mendapatkan solusi terbaik dari suatu masalah yang terdefinisi dengan baik (Krishnamoorthy et al, 2019;Wu et al, 2018). Metode optimasi digunakan di banyak bidang studi untuk menemukan solusi yang memaksimalkan atau meminimalkan beberapa parameter studi, seperti meminimalkan biaya dalam produksi suatu barang atau jasa, memaksimalkan keuntungan, meminimalkan bahan baku dalam pengembangan suatu barang, atau memaksimalkan produksi (Aisyahna et al, 2020).…”

Section: Tinjauan Pustakaunclassified

Aplikasi Non Linear Univariabel Dalam Optimasi Material Blanksheet Proses Stamping Pada Industri Kendaraan Bermotor Roda Empat

Semnasti,

Semnasti

et al. 2023

waluyojatmiko

View full text Add to dashboard Cite

Dewasa ini perkembangan bisnis memasuki era baru dimana perusahaan dituntut untuk meningkatkan performanya agar mampu bersaing dipasar global. Salah satunya adalah industri manufaktur otomotif yang memproduksi kendaraan roda empat termasuk mobil. Kondisi persaingan bisnis di bidang manufaktur otomotif dalam pasar global semakin ketat. Namun, terjadi penurunan selama pandemic covid-19. Setelah melewati pandemic covid-19, persaingan menuntut organisasi untuk terus melakukan cost reduction di segala bidang, dimana cost terbesar dari departemen Stamping adalah material cost yaitu sebesar 60% dari semua biaya. Tujuan penelitian ini adalah untuk melakukan optimasi pada kebutuhan material agar didapatkan biaya yang rendah. Penelitian ini mengaplikasikan optimasi non linear univariabel. Tahapan sistematis yang digunakan yaitu Plan, Do, Check, Action (PDCA). Hasil penelitian menunjukkan terjadinya perubahan size blanksheet dari 165 cm menjadi 152,48 cm sehingga didapat didapat penurunan biaya (cost reduction) sebesar 760.692.829 per tahun atau penurunan jumlah scrap dari 0,945 kg menjadi 0,425 kg.

show abstract

Section: Tinjauan Pustakaunclassified

Aplikasi Non Linear Univariabel Dalam Optimasi Material Blanksheet Proses Stamping Pada Industri Kendaraan Bermotor Roda Empat

Semnasti,

Semnasti

et al. 2023

waluyojatmiko

View full text Add to dashboard Cite

show abstract

“…The suppliers collect the parts and transport them to the assembly plants in the small-batch and multi-frequency mode. A multi-factory Milk run pickup problem with uncertain demand and frequency in China's automobile industry is presented in (Wu, 2018). Considering the balance between inventory cost and distribution cost, a mixed-integer programming model was built for this problem and converted into a robust optimization model by the Chernoff-Hoeffding theorem.…”

Section: Materials Flow and Related Workmentioning

confidence: 99%

Modelling material flow using the Milk run and Kanban systems in the automotive industry

Simić

Svirčević²,

Corchado

et al. 2020

Expert Systems

View full text Add to dashboard Cite

Material flow management refers to the analysis and specific optimization of the inventory-production system. Material flow can be characterized as the organized flow of material in a production process with the required sequence determined by a technological procedure. The Milk run system assures the transportation of materials at the right time and in an optimal manner. It should be combined with the Kanban system to highlight when something is required in the production process. This paper presents biological swarm intelligence, in general, and a particular model, particle swarm optimization (PSO), for modelling material flow using a Milk run system supported by a Kanban system in the automotive industry. The aim of this study is to create a new model for the optimal number of trailers for one train and optimal number of containers in a tugger train system when the route time period has been defined. A new modified PSO approach for integrating inventory-production in a unique optimization model is used. The major modification to the original PSO is using the capacity of a container instead of a velocity component. Each new Kanban trigger is checked, and the total timing for the Milk run delivery solution is calculated for the necessary raw material capacity for each shop floor.

show abstract

“…In an automotive parts milk-run network, a logistics company develops efficient parts pick-up plans based on parts purchase orders of automotive manufacturers and corresponding parts supplier networks and arranges for several empty trucks to visit a few suppliers from the depot, collect a predetermined number of parts, and deliver them back to the depot to fulfill assembly line requirements. This process is often modeled as the classic Capacitated Vehicle Routing Problem (CVRP) [2][3][4][5][6][7][8][9]. With the increasing industrial concentration and scale of the automotive industry in China and worldwide, automotive parts suppliers are gradually clustering in industrial parks located in various cities, forming supplier clusters, which has a subtle impact on automotive parts logistics activities.…”

Section: Introductionmentioning

confidence: 99%

A Two-Level Variable Neighborhood Descent for a Split Delivery Clustered Vehicle Routing Problem with Soft Cluster Conflicts and Customer-Related Costs

Huang

Wei

2023

Sustainability

View full text Add to dashboard Cite

This paper introduces Split Delivery Clustered Vehicle Routing Problem with Soft cluster conflicts and Customer-related costs (SDCVRPSC) arising in automotive parts of milk-run logistics with supplier cluster distribution in China. In SDCVRPSC, customers are divided into different clusters that can be visited by multiple vehicles, but each vehicle can only visit each cluster once. Penalty costs are incurred when traveling between clusters. The transportation cost of a route is calculated as the maximum direct shipment cost between customers on the route plus the total drop costs. The SDCVRPSC aims to minimize the sum of transportation costs and penalty costs by determining the assignment of customers to vehicles and the visiting order of clusters. We propose an integer linear programming model and a two-level variable neighborhood descent algorithm (TLVND) that includes two-stage construction, intensification at cluster and customer levels, and a perturbation mechanism. Experimental results on designed SDCVRPSC benchmark instances demonstrate that TLVND outperforms the Gurobi solver and two adapted algorithms at the business operation level. Moreover, a real case study indicates that TLVND can bring significant economic savings compared to expert experience decisions. TLVND has been integrated into the decision support system of the case company for daily operations.

show abstract

A robust hybrid heuristic algorithm to solve multi-plant milk-run pickup problem with uncertain demand in automobile parts industry

Cited by 11 publications

References 20 publications

Aplikasi Non Linear Univariabel Dalam Optimasi Material Blanksheet Proses Stamping Pada Industri Kendaraan Bermotor Roda Empat

Aplikasi Non Linear Univariabel Dalam Optimasi Material Blanksheet Proses Stamping Pada Industri Kendaraan Bermotor Roda Empat

Modelling material flow using the Milk run and Kanban systems in the automotive industry

A Two-Level Variable Neighborhood Descent for a Split Delivery Clustered Vehicle Routing Problem with Soft Cluster Conflicts and Customer-Related Costs

Contact Info

Product

Resources

About