scholarly journals Customer-Oriented Vehicle Routing Problem with Environment Consideration: Two-Phase Optimization Approach and Heuristic Solution

2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Fanting Meng ◽  
Yong Ding ◽  
Wenjie Li ◽  
Rongge Guo
Keyword(s):  
Vehicle Routing ◽  
Fuel Consumption ◽  
Vehicle Routing Problem ◽  
Optimization Method ◽  
Second Phase ◽  
Optimization Approach ◽  
Two Phase ◽  
Routing Problem ◽  
Problem Model ◽  
Phase Optimization

With the fastest consumer demand growth, the increasing customer’s demands trend to multivarieties and small-batch and the customer requires an efficient distribution planning. How to plan the vehicle route to meet customer satisfaction of mass distribution as well as reduce the fuel consumption and emission has become a hot topic. This paper proposes a two-phase optimization method to handle the vehicle routing problem, considering the customer demands and time windows coupled with multivehicles. The first phase of the optimization method provides a fuzzy hierarchical clustering method for customer grouping. The second phase formulates the optimization en-group vehicle routing problem model and a genetic algorithm to account for vehicle routing optimization within each group so that fuel consumption and emissions are minimized. Finally, we provide some numerical examples. Results show that the two-phase optimization method and the designed algorithm are efficient.

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

scholarly journals Performance Comparison of Two-phase LP-based Heuristic Methods for Capacitated Vehicle Routing Problem with Three Objectives

2020 ◽  
Vol 24 (5) ◽  
pp. 145-159
Author(s):  
Sophea Horng ◽  
Pisal Yenradee
Keyword(s):  
Vehicle Routing ◽  
Fuel Consumption ◽  
Vehicle Routing Problem ◽  
Experimental Results ◽  
Personal Relationships ◽  
Heuristic Methods ◽  
Two Phase ◽  
Routing Problem ◽  
Clustering Model ◽  
Capacitated Vehicle

This paper develops a two-phase LP-based heuristic for the Capacitated Vehicle Routing Problem (CVRP). It considers three objectives: (1) minimizing the total costs of fuel consumption and overtime, (2) maximizing the total personal relationships between customers and drivers, and (3) balancing the delivery weights of vehicles. The two-phase LP-based heuristic (cluster-first route-second) is proposed. First, in the clustering stage, three LP-based clustering models (denoted by C1, C2, and C3) are developed. Customers are grouped into clusters based on real distances between the customers for C1, personal relationships between the customers and drivers for C2, and the delivery weights of vehicles for C3. Second, in the routing stage, an LP-based traveling salesman problem model is used to form a route for each cluster, to minimize the total costs of fuel consumption and overtime labor. The experimental results from a case study of Thai SMEs show that when the C2 clustering model is applied, the performances are the best. Significant contributions of this paper include: (1) it is an original paper that proposes the C2 clustering model, and it has the best performances based on the experimental results, and (2) the proposed two-phase LP-based heuristic methods are suitable for practical use by SMEs since the required computational time is short, and it has multiple models with different objectives that can be selected to match a user's requirements.

scholarly journals A Simulated Annealing Algorithm for Solving Two-Echelon Vehicle Routing Problem with Locker Facilities

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 218
Author(s):  
A. A. N. Perwira Redi ◽  
Parida Jewpanya ◽  
Adji Candra Kurniawan ◽  
Satria Fadil Persada ◽  
Reny Nadlifatin ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Simulated Annealing Algorithm ◽  
Two Phase ◽  
Routing Problem ◽  
Intermediate Facilities ◽  
Annealing Algorithm ◽  
Phase Optimization ◽  
The Cost

We consider the problem of utilizing the parcel locker network for the logistics solution in the metropolitan area. Two-echelon distribution systems are attractive from an economic standpoint, whereas the product from the depot can be distributed from or to intermediate facilities. In this case, the intermediate facilities are considered as locker facilities present in an accessible location in the vicinity of the final customers. In addition, the utilization of locker facilities can reduce the cost caused by the unattended deliveries. The problem is addressed as an optimization model that formulated into an integer linear programming model denoted as the two-echelon vehicle routing problem with locker facilities (2EVRP-LF). The objective is to minimize the cost of transportation with regards to the vehicle travelling cost, the intermediate facilities renting cost, and the additional cost to compensate the customer that needs to travel to access the intermediate facilities. Because of its complexity, a simulated annealing algorithm is proposed to solve the problem. On the other hand, the modelling approach can be conducted by generating two-phase optimization model approaches, which are the p-median problem and the capacitated vehicle routing problem. The results from both methods are compared in numerical experiments. The results show the effectiveness of 2EVRP-LF compared to the two-phase optimization. Furthermore, the simulated annealing algorithm showed an effective performance in solving 2EVRP-LF.

A Shuffled Frog Leaping Algorithm for Solving Vehicle Routing Problem

2012 ◽  
Vol 197 ◽  
pp. 529-533 ◽  
Author(s):  
Kai Ping Luo
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
High Efficiency ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Shuffled Frog Leaping Algorithm ◽  
Routing Problem ◽  
Shuffled Frog Leaping ◽  
Encoding Method ◽  
Nearest Neighborhood

For vehicle routing problem, its model is easy to state and difficult to solve. The shuffled frog leaping algorithm is a novel meta-heuristic optimization approach and has strong quickly optimal searching power. The paper applies herein this algorithm to solve the vehicle routing problem; presents a high-efficiency encoding method based on the nearest neighborhood list; improves evolution strategies of the algorithm in order to keep excellent characteristics of the best frog. This proposed algorithm provides a new idea for solving VRP.

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 A Hybrid Ant Colony Optimization for Dynamic Multidepot Vehicle Routing Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Haitao Xu ◽  
Pan Pu ◽  
Feng Duan
Keyword(s):  
Ant Colony Optimization ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony ◽  
Optimization Approach ◽  
Dynamic Vehicle Routing ◽  
Routing Problem ◽  
Multiple Depots ◽  
Mutation Operation ◽  
Clustering Approach

In the real world, the vehicle routing problem (VRP) is dynamic and variable, so dynamic vehicle routing problem (DVRP) has obtained more and more attentions among researchers. Meanwhile, due to actual constraints of service hours and service distances, logistics companies usually build multiple depots to serve a great number of dispersed customers. Thus, the research of dynamic multidepot vehicle routing problem (DMDVRP) is significant and essential. However, it has not attracted much attention. In this paper, firstly, a clustering approach based on the nearest distance is proposed to allocate all customers to the depots. Then a hybrid ant colony optimization (HACO) with mutation operation and local interchange is introduced to optimize vehicle routes. In addition, in order to deal with dynamic problem of DMDVRP quickly, a real-time addition and optimization approach is designed to handle the new customer requests. Finally, the t-test is applied to evaluate the proposed algorithm; meanwhile the relations between degrees of dynamism (dod) and HACO are discussed minutely. Experimental results show that the HACO algorithm is feasible and efficient to solve DMDVRP.

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