Fourth party logistics routing problem model with fuzzy duration time and cost discount

2013 ◽  
Vol 50 ◽  
pp. 14-24 ◽  
Author(s):  
Yan Cui ◽  
Min Huang ◽  
Shengxiang Yang ◽  
Loo Hay Lee ◽  
Xingwei Wang
Keyword(s):  
Routing Problem ◽  
Problem Model ◽  
Duration Time ◽  
Fourth Party Logistics ◽  
Cost Discount

Fourth party logistics routing problem with fuzzy duration time

2013 ◽  
Vol 145 (1) ◽  
pp. 107-116 ◽  
Author(s):  
Min Huang ◽  
Yan Cui ◽  
Shengxiang Yang ◽  
Xingwei Wang
Keyword(s):  
Routing Problem ◽  
Duration Time ◽  
Fourth Party Logistics

A Multi-Period Evacuation Vehicle Routing Problem Model

2014 ◽  
Vol 931-932 ◽  
pp. 578-582
Author(s):  
Sunarin Chanta ◽  
Ornurai Sangsawang
Keyword(s):  
Vehicle Routing ◽  
Public Transportation ◽  
Vehicle Routing Problem ◽  
Programming Model ◽  
High Water ◽  
Mixed Integer ◽  
Routing Problem ◽  
Problem Model ◽  
Proposed Model ◽  
Evacuation Routing

In this paper, we proposed an optimization model that addresses the evacuation routing problem for flood disaster when evacuees trying to move from affected areas to safe places using public transportation. A focus is on the situation of evacuating during high water level when special high vehicles are needed. The objective is to minimize the total traveled distance through evacuation periods where a limited number of vehicles is given. We formulated the problem as a mixed integer programming model based on the capacitated vehicle routing problem with multiple evcuation periods where demand changing by the time. The proposed model has been tested on a real-world case study affected by the severe flooding in Thailand, 2011.

scholarly journals Capacitated vehicle routing problem model for carriers

2018 ◽  
Vol 12 ◽  
Author(s):  
Irma-Delia Rojas-Cuevas ◽  
Santiago-Omar Caballero-Morales ◽  
Jose-Luis Martinez-Flores ◽  
Jose-Rafael Mendoza-Vazquez
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Network Flow ◽  
Route Planning ◽  
Test Problems ◽  
Optimal Route ◽  
Routing Problem ◽  
Problem Model ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Background: The Capacitated Vehicle Routing Problem (CVRP) is one of the most important transportation problems in logistics and supply chain management. The standard CVRP considers a fleet of vehicles with homogeneous capacity that depart from a warehouse, collect products from (or deliver products to) a set of customer locations (points) and return to the same warehouse. However, the operation of carrier companies and third-party transportation providers may follow a different network flow for collection and delivery. This may lead to non-optimal route planning through the use of the standard CVRP.Objective: To propose a model for carrier companies to obtain optimal route planning.Method: A Capacitated Vehicle Routing Problem for Carriers (CVRPfC) model is used to consider the distribution scenario where a fleet of vehicles depart from a vehicle storage depot, collect products from a set of customer points and deliver them to a specific warehouse before returning to the vehicle storage depot. Validation of the model’s functionality was performed with adapted CVRP test problems from the Vehicle Routing Problem LIBrary. Following this, an assessment of the model’s economic impact was performed and validated with data from a real carrier (real instance) with the previously described distribution scenario.Results: The route planning obtained through the CVRPfC model accurately described the network flow of the real instance and significantly reduced its distribution costs.Conclusion: The CVRPfC model can thus improve the competitiveness of the carriers by providing better fares to their customers, reducing their distribution costs in the process.

scholarly journals The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Fuqiang Lu ◽  
Wenjing Feng ◽  
Mengying Gao ◽  
Hualing Bi ◽  
Suxin Wang
Keyword(s):  
Ant Colony ◽  
Third Party ◽  
Destination Node ◽  
Problem Analysis ◽  
Ant Colony System ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Routing Problem ◽  
Initial Node ◽  
Fourth Party Logistics

The fourth-party logistics routing problem (4PLRP) is an important issue in the operation of fourth-party logistics (4PL). In this paper, the study of fourth-party logistics (4PL) path optimization considers that more third-party logistics (3PL) undertake transportation tasks. Under the condition that the 3PL transportation time, transportation cost, node transit time, and transit cost are uncertain, 4PL provides customers with a set of transportation solutions to transport transportation tasks from the initial node to the destination node according to the customer’s risk aversion preference. The transportation scheme not only meets the customer’s time and cost requirements but also meets the carrying capacity and reputation constraints of 3PL. Between the two nodes, one or more 3PLs will undertake the transportation task. The customer’s risk preference will be measured by the ratio utility theory (RUT). An ant colony system-improved grey wolf optimization (ACS-IGWO) is designed to solve the model, and the grey wolf optimization (GWO) is improved by the convergence factor and the proportional weight. Problem analysis is conducted through simulation experiments.

scholarly journals Flow Merging and Hub Route Optimization in Collaborative Transportation

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Kerui Weng ◽  
Zi-hao Xu
Keyword(s):  
Integer Programming ◽  
Lagrangian Relaxation ◽  
Benders Decomposition ◽  
Programming Model ◽  
Route Optimization ◽  
Mixed Integer ◽  
Routing Problem ◽  
Fixed Charges ◽  
Postal Services ◽  
Cost Discount

This paper studies the optimal hub routing problem of merged tasks in collaborative transportation. This problem allows all carriers’ transportation tasks to reach the destinations optionally passing through 0, 1, or 2 hubs within limited distance, while a cost discount on arcs in the hub route could be acquired after paying fixed charges. The problem arises in the application of logistics, postal services, airline transportation, and so forth. We formulate the problem as a mixed-integer programming model, and provide two heuristic approaches, respectively, based on Lagrangian relaxation and Benders decomposition. Computational experiments show that the algorithms work well.

scholarly journals PERENCANAAN JADWAL DAN RUTE DISTRIBUSI ROKOK UNTUK MENEKAN TOTAL BIAYA TRANSPORTASI

2012 ◽  
Vol 13 (2) ◽  
pp. 151 ◽  
Author(s):  
Thomy Eko Saputro ◽  
Aprilia Prihatina
Keyword(s):  
Vehicle Routing ◽  
Customer Service ◽  
Vehicle Routing Problem ◽  
Optimization Method ◽  
Distribution Area ◽  
Nearest Neighbour ◽  
Routing Problem ◽  
Problem Model ◽  
Periodic Vehicle Routing Problem ◽  
Periodic Vehicle Routing

Thomy Eko Saputro DAN Aprilia PrihatinaJurusan Teknik Industri, Fakultas Teknik, Universitas Muhammadiyah MalangLaman: [email protected] satu hal yang berpengaruh dalam meningkatkan pelayanan konsumen adalah bagaimana mengirimkan produkyang tepat waktu kepada seluruh konsumen. Oleh karena itu pelaku bisnis perlu menerapkan suatu strategi yang tepat agardapat mengefisienkan dan mengefektifkan proses distribusinya. PR 567 sebagai distributor rokok perwakilan Purwodadiberupaya agar pendistribusian berjalan dengan baik karena mengingat proses distribusi dengan jumlah agen yang cukupbanyak seringkali mempersulit distributor untuk menentukan jadwal dan rute yang tepat. Permasalahan pendistribusianini termasuk dalam PVRP (Periodic Vehicle Routing Problem). Penyelesaian dilakukan menggunakan metode clusterfirst-second route dengan penugasan agen ke hari kunjungan menggunakan metode optimasi. Solusi akhir nantinyaakan memberikan jadwal dan rute kendaraan dengan total biaya tranportasi yang paling minimum. Pada penelitian iniwilayah distribusi dibagi menjadi 2 cluster dan dari penyelesaian model PVRP diperoleh frekuensi kunjungan yang tepatuntuk cluster 1 adalah sebanyak sekali dalam seminggu. Sedangkan untuk cluter 2 dikunjungi sebanyak 3 kali dalamseminggu. Hasil penentuan jadwal dan rute dari penelitian inimemberikan total biaya transportasi sebesar Rp725.805per minggu. Dengan kata lain terjadi penghematan sebesar Rp320.189/minggu atau menghemat sebesar 44% per minggudari biaya awal yang harus dikeluarkan.Kata kunci: Vehicle routing, periodic, nearest neighbour, optimasiABSTRACTOne of the main issue in improving the customer service is how to deliver the product on time to customers. Therefore,the stakeholders need to apply an appropriate strategy in order to make distribustion process become more efficient andeffective. Because it is hard to determine appropriate schedule and route when dealing with a lot agents, PR 567 as arepresentative distributor of cigarette in Purwodadi attempts to make its distribution process better. This was done by usingPVRP (Periodic Vehicle Routing Problem) model with cluster first-second route approach and optimization method forassigning vehicle. The result of this research were frequency, schedule, and route with the most minimum transportationcost. In this research, the distribution area was defined into two cluster. The best delivery frequency for cluster one was onceweek, while cluster two was three times a week. The transportation cost was Rp725805/week. In the other hand, the savingcost was Rp320189/week or 44%/week from the initial cost.Key words: Vehicle routing, periodic, nearest neighbour, optimization

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