scholarly journals Container Swap Trailer Transportation Routing Problem Based on Genetic Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Hua-wei Ma ◽  
Lei Tao ◽  
Xiao-xuan Hu
Keyword(s):  
Genetic Algorithm ◽  
Time Window ◽  
Programming Model ◽  
Routing Problem ◽  
Adjustment Policy ◽  
Organization Mode ◽  
Adaptive Adjustment ◽  
Transportation Routing ◽  
Time Window Constraints ◽  
Self Adaptive

In swap trailer transportation routing problems, trucks and trailers conduct swap operations at special positions called trailer points. The parallelization of stevedoring and transportation can be achieved by means of these trailer points. This logistics organization mode can be more effective than the others. In this paper, an integer programming model with capacity and time-window constraints was established. A repairing strategy is embedded in the genetic algorithm (GA) to solve the model. The repairing strategy is executed after the crossover and mutation operation to eliminate the illegal routes. Furthermore, a parameter self-adaptive adjustment policy is designed to improve the convergence. Then numerical experiments are implemented based on the generated datasets; the performance and robustness of the algorithm parameter self-adaptive adjustment policy are discussed. Finally, the results show that the improved algorithm performs better than elementary GA.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

scholarly journals Model of Flexible Periodic Vehicle Routing Problem-Service Choice Considering Inventory Status

2021 ◽  
Vol 22 (1) ◽  
pp. 125-137
Author(s):  
Muhammad Alde Rizal ◽  
Ifa Saidatuningtyas
Keyword(s):  
Mathematical Model ◽  
Vehicle Routing ◽  
Time Window ◽  
Programming Model ◽  
Mixed Integer ◽  
Routing Problem ◽  
Inventory Costs ◽  
Delivery Times ◽  
Periodic Vehicle Routing Problem ◽  
Time Window Constraints

Vehicle routing problems and inventory problems need to be integrated in order to improve performance. This research discusses the determination of vehicle routes for product delivery with periodic delivery times that are released at any time depending on the inventory status. A mixed-integer linear programming model in determining periodic flexible visiting vehicles' route considering inventory is proposed to solve this problem. This model also accommodates time window constraints, retailer warehouse capacity. The search for solutions was carried out using the branch-and-bound method with the help of Lingo 18.0. The mathematical model testing result saves shipping costs and inventory costs. In addition, the developing mathematical model offers the flexibility of visiting depending on the inventory status of the consumer. The sensitivity analysis of the model results in the vehicle capacity influence the total cost and routes formed.

A New Multi-Criteria Solving Procedure for Multi-Depot FSM-VRP with Time Window

2017 ◽  
Vol 4 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Lahcene Guezouli ◽  
Samir Abdelhamid
Keyword(s):  
Genetic Algorithm ◽  
Combinatorial Optimization ◽  
Vehicle Routing Problem ◽  
Processing Time ◽  
Optimization Problems ◽  
Time Window ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
Acceptable Quality ◽  
Capacitated Vehicle

One of the most important combinatorial optimization problems is the transport problem, which has been associated with many variants such as the HVRP and dynamic problem. The authors propose in this study a decision support system which aims to optimize the classical Capacitated Vehicle Routing Problem by considering the existence of different vehicle types (with distinct capacities and costs) and multiple available depots, that the authors call the Multi-Depot HVRPTW by respecting a set of criteria including: schedules requests from clients, the heterogeneous capacity of vehicles..., and the authors solve this problem by proposing a new scheme based on a genetic algorithm heuristics that they will specify later. Computational experiments with the benchmark test instances confirm that their approach produces acceptable quality solutions compared with previous results in similar problems in terms of generated solutions and processing time. Experimental results prove that the method of genetic algorithm heuristics is effective in solving the MDHVRPTW problem and hence has a great potential.

Recent progress of local search in handling the time window constraints of the vehicle routing problem

4OR ◽  
2010 ◽  
Vol 8 (3) ◽  
pp. 221-238 ◽  
Author(s):  
Hideki Hashimoto ◽  
Mutsunori Yagiura ◽  
Shinji Imahori ◽  
Toshihide Ibaraki
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Recent Progress ◽  
Time Window ◽  
Routing Problem ◽  
Time Window Constraints

scholarly journals Matheuristics and Column Generation for a Basic Technician Routing Problem

Algorithms ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 313
Author(s):  
Nicolas Dupin ◽  
Rémi Parize ◽  
El-Ghazali Talbi
Keyword(s):  
Machine Learning ◽  
Column Generation ◽  
Time Window ◽  
Time Windows ◽  
Machine Learning Techniques ◽  
Mixed Integer ◽  
Routing Problems ◽  
Routing Problem ◽  
Feasible Solutions ◽  
Time Window Constraints

This paper considers a variant of the Vehicle Routing Problem with Time Windows, with site dependencies, multiple depots and outsourcing costs. This problem is the basis for many technician routing problems. Having both site-dependency and time window constraints lresults in difficulties in finding feasible solutions and induces highly constrained instances. Matheuristics based on Mixed Integer Linear Programming compact formulations are firstly designed. Column Generation matheuristics are then described by using previous matheuristics and machine learning techniques to stabilize and speed up the convergence of the Column Generation algorithm. The computational experiments are analyzed on public instances with graduated difficulties in order to analyze the accuracy of algorithms for ensuring feasibility and the quality of solutions for weakly to highly constrained instances. The results emphasize the interest of the multiple types of hybridization between mathematical programming, machine learning and heuristics inside the Column Generation framework. This work offers perspectives for many extensions of technician routing problems.

scholarly journals VEHICLE ROUTING PROBLEM WITH TIME WINDOWS USING HYBRID ENCODING GENETIC ALGORITHM

2014 ◽  
Vol 12 (10) ◽  
pp. 3945-3951
Author(s):  
Dr P.K Chenniappan ◽  
Mrs.S.Aruna Devi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Time Windows ◽  
Minimal Cost ◽  
Total Size ◽  
Routing Problem ◽  
Time Window Constraints ◽  
Vehicle Capacity ◽  
Vehicle Routes

The vehicle routing problem is to determine K vehicle routes, where a route is a tour that begins at the depot, traverses a subset of the customers in a specified sequence and returns to the depot. Each customer must be assigned to exactly one of the K vehicle routes and total size of deliveries for customers assigned to each vehicle must not exceed the vehicle capacity. The routes should be chosen to minimize total travel cost. Thispapergivesasolutiontofindanoptimumrouteforvehicle routingproblem using Hybrid Encoding GeneticAlgorithm (HEGA)technique tested on c++ programming.The objective is to find routes for the vehicles to service all the customers at a minimal cost and time without violating the capacity, travel time constraints and time window constraints

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