scholarly journals Route Optimization for the Distribution Network of a Confectionary Chain

2015 ◽  
Vol 27 (6) ◽  
pp. 497-503
Author(s):  
Anıl İnanlı ◽  
Başak Ünsal ◽  
Deniz Türsel Eliiyi
Keyword(s):  
Time Windows ◽  
Distribution Network ◽  
Real Data ◽  
Route Optimization ◽  
Routing Problem ◽  
Hard Time ◽  
Np Hard Problem ◽  
Commercial Solver ◽  
High Level ◽  
The Cost

This study considers the distribution network of a well-known perishable food manufacturer and its franchises in Turkey. As the countrywide number of stores is increasing fast, the company is facing problems due to its central distribution of products from a single factory. The objective is to decrease the cost of transportation while maintaining a high level of customer satisfaction. Hence, the focus is on the vehicle routing problem (VRP) of this large franchise chain within each city. The problem is defined as a rich VRP with heterogeneous fleet, site-dependent and compartmentalized vehicles, and soft/hard time windows. This NP-hard problem is modelled and tried with real data on a commercial solver. A basic heuristic procedure which can be used easily by the decision makers is also employed for obtaining quick and high-quality solutions for large instances.

scholarly journals An Effective Approach for the Multiobjective Regional Low-Carbon Location-Routing Problem

2019 ◽  
Vol 16 (11) ◽  
pp. 2064 ◽  
Author(s):  
Longlong Leng ◽  
Yanwei Zhao ◽  
Jingling Zhang ◽  
Chunmiao Zhang
Keyword(s):  
Time Windows ◽  
Mixed Integer ◽  
Low Carbon ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Domain Specific ◽  
Hard Time ◽  
Selection Strategies ◽  
Location Routing ◽  
High Level

In this paper, we consider a variant of the location-routing problem (LRP), namely the the multiobjective regional low-carbon LRP (MORLCLRP). The MORLCLRP seeks to minimize service duration, client waiting time, and total costs, which includes carbon emission costs and total depot, vehicle, and travelling costs with respect to fuel consumption, and considers three practical constraints: simultaneous pickup and delivery, heterogeneous fleet, and hard time windows. We formulated a multiobjective mixed integer programming formulations for the problem under study. Due to the complexity of the proposed problem, a general framework, named the multiobjective hyper-heuristic approach (MOHH), was applied for obtaining Pareto-optimal solutions. Aiming at improving the performance of the proposed approach, four selection strategies and three acceptance criteria were developed as the high-level heuristic (HLH), and three multiobjective evolutionary algorithms (MOEAs) were designed as the low-level heuristics (LLHs). The performance of the proposed approach was tested for a set of different instances and comparative analyses were also conducted against eight domain-tailored MOEAs. The results showed that the proposed algorithm produced a high-quality Pareto set for most instances. Additionally, extensive analyses were also carried out to empirically assess the effects of domain-specific parameters (i.e., fleet composition, client and depot distribution, and zones area) on key performance indicators (i.e., hypervolume, inverted generated distance, and ratio of nondominated individuals). Several management insights are provided by analyzing the Pareto solutions.

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

scholarly journals A Heuristics-Based Parthenogenetic Algorithm for the VRP with Potential Demands and Time Windows

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Chenghua Shi ◽  
Tonglei Li ◽  
Yu Bai ◽  
Fei Zhao
Keyword(s):  
Genetic Algorithm ◽  
Time Windows ◽  
Computation Time ◽  
Routing Problem ◽  
Split Delivery ◽  
Soft Time Windows ◽  
Comparison Results ◽  
Potential Demand ◽  
The Cost

We present the vehicle routing problem with potential demands and time windows (VRP-PDTW), which is a variation of the classical VRP. A homogenous fleet of vehicles originated in a central depot serves customers with soft time windows and deliveries from/to their locations, and split delivery is considered. Also, besides the initial demand in the order contract, the potential demand caused by conformity consuming behavior is also integrated and modeled in our problem. The objective of minimizing the cost traveled by the vehicles and penalized cost due to violating time windows is then constructed. We propose a heuristics-based parthenogenetic algorithm (HPGA) for successfully solving optimal solutions to the problem, in which heuristics is introduced to generate the initial solution. Computational experiments are reported for instances and the proposed algorithm is compared with genetic algorithm (GA) and heuristics-based genetic algorithm (HGA) from the literature. The comparison results show that our algorithm is quite competitive by considering the quality of solutions and computation time.

Przegląd czynników wpływających na skuteczność nawaniania gazu

Nafta-Gaz ◽  
2021 ◽  
Vol 77 (8) ◽  
pp. 553-560
Author(s):  
Anna Huszał ◽  
Keyword(s):  
Distribution Network ◽  
Field Measurements ◽  
International Standards ◽  
Odor Intensity ◽  
Operational Experience ◽  
Minimum Concentration ◽  
Gas Network ◽  
Natural Gases ◽  
High Level ◽  
The Cost

Due to rapid advancement in technology, the odorization process in Poland seems to be increasingly stabilized in practice and conducted at a sufficiently high level. International standards are adopted in this regard. One of the most important requirements for the natural gases quality delivered to customers from a distribution network, guaranteeing their safe use is ensuring an appropriate odorization level, allowing to detect the uncontrolled gas leakages from the distribution network, installation and gas appliances. The odorant concentration in its dosing point should ensure the intensity of the gas odor at the “clearly perceptible” level at the network end point. The odorant concentration variability in the gas network is a dynamic value, constantly accompanying the odorizing process. In consequence constant metrological supervision over the process is needed (what might be done by measuring the odorant concentration and gas odor intensity). Also, verification of undergoing periodic changes in the value of the minimum concentration of odorant in the gas for the respective groups of natural gases and various gas pipelines based on operational experience and field measurements is required. Such verification allows to determine the optimal concentration of odorant for each group of natural gases and furthermore allows to optimize the cost of gas odorization process while ensuring its legally required quality described as odor intensity. This article presents the problem of the dependence of the network gas odorization effectiveness on various factors, especially network parameters or even the gas composition itself. Their identification allows to better plan the process and ensure its effective implementation, which ultimately ensures safety for gas users.

The Research on VRP Based on Max-Min Ant Colony Algorithm

2011 ◽  
Vol 219-220 ◽  
pp. 1285-1288 ◽  
Author(s):  
Chang Min Chen ◽  
Wei Cheng Xie ◽  
Song Song Fan
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Search Time ◽  
Ant Colony ◽  
Local Optimum ◽  
Simulation Data ◽  
Routing Problem ◽  
Np Hard Problem ◽  
The Cost

Vehicle routing problem (VRP) is the key to reducing the cost of logistics, and also an NP-hard problem. Ant colony algorithm is a very effective method to solve the VRP, but it is easy to fall into local optimum and has a long search time. In order to overcome its shortcomings, max-min ant colony algorithm is adopted in this paper, and its simulation system is designed in GUI of MATLAB7.0. The results show that the vehicle routing problem can well achieves the optimization of VRP by accessing the simulation data of database.

BFO Optimization Algorithms for Vehicle Routing Problem with Time Windows

2014 ◽  
Vol 543-547 ◽  
pp. 1884-1887
Author(s):  
Li Jing Tan ◽  
Fu Yong Lin ◽  
Hong Wang
Keyword(s):  
Convergence Rate ◽  
Swarm Intelligence ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Hard Problem ◽  
Rapid Convergence ◽  
Bacterial Foraging Optimization ◽  
Routing Problem ◽  
Np Hard Problem

Vehicle Routing Problem with Time Windows (VRPTW) is a constrained NP-hard problem that designs the least cost routes from one depot to a set of geographically scattered points. Most of traditional techniques are difficult to solve this kind of problem. In this paper, we explored the validity of another swarm-intelligence-based model-Bacterial Foraging Optimization (BFO) for VRPTW solving. Original BFO, BFO with linear decreasing chemotaxis step (BFO-LDC) and BFO with non-linear decreasing chemotaxis step (BFO-NDC) are used to obtain the best solutions of a given VRPTW problem, respectively. The experimental results demonstrated that the proposed BFO algorithms have the potential to solve Vehicle Routing Problem with Time Windows (VRPTW) with rapid convergence rate and the good result accuracy.

Sign in / Sign up

Export Citation Format

Share Document