scholarly journals The Optimization of Transportation Costs in Logistics Enterprises with Time-Window Constraints

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Qingyou Yan ◽  
Qian Zhang
Keyword(s):  
Arrival Time ◽  
Time Window ◽  
Transportation Cost ◽  
Transportation Costs ◽  
Routing Problem ◽  
Fleet Size ◽  
Inventory Costs ◽  
Penalty Costs ◽  
Total Transportation Cost ◽  
Time Window Constraints

This paper presents a model for solving a multiobjective vehicle routing problem with soft time-window constraints that specify the earliest and latest arrival times of customers. If a customer is serviced before the earliest specified arrival time, extra inventory costs are incurred. If the customer is serviced after the latest arrival time, penalty costs must be paid. Both the total transportation cost and the required fleet size are minimized in this model, which also accounts for the given capacity limitations of each vehicle. The total transportation cost consists of direct transportation costs, extra inventory costs, and penalty costs. This multiobjective optimization is solved by using a modified genetic algorithm approach. The output of the algorithm is a set of optimal solutions that represent the trade-off between total transportation cost and the fleet size required to service customers. The influential impact of these two factors is analyzed through the use of a case study.

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.

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 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 An Inverse Robust Optimisation Approach for a Class of Vehicle Routing Problems under Uncertainty

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Liang Sun ◽  
Bing Wang
Keyword(s):  
Vehicle Routing ◽  
Transportation Cost ◽  
Test Problems ◽  
Vehicle Routing Problems ◽  
Road Transportation ◽  
Robust Optimisation ◽  
Routing Problems ◽  
Routing Problem ◽  
Trade Off ◽  
Total Transportation Cost

There is a trade-off between the total penalty paid to customers (TPC) and the total transportation cost (TTC) in depot for vehicle routing problems under uncertainty (VRPU). The trade-off refers to the fact that the TTC in depot inevitably increases when the TPC decreases andvice versa. With respect to this issue, the vehicle routing problem (VRP) with uncertain customer demand and travel time was studied to optimise the TPC and the TTC in depot. In addition, an inverse robust optimisation approach was proposed to solve this kind of VRPU by combining the ideas of inverse optimisation and robust optimisation so as to improve both the TPC and the TTC in depot. The method aimed to improve the corresponding TTC of the robust optimisation solution under the minimum TPC through minimising the adjustment of benchmark road transportation cost. According to the characteristics of the inverse robust optimisation model, a genetic algorithm (GA) and column generation algorithm are combined to solve the problem. Moreover, 39 test problems are solved by using an inverse robust optimisation approach: the results show that both the TPC and TTC obtained by using the inverse robust optimisation approach are less than those calculated using a robust optimisation approach.

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 Optimization in Determining Routes of Goods Distribution Vehicle Using the Ant Colony Optimization Algorithm Method at PT XYZ

2020 ◽  
Vol 2 (1) ◽  
pp. 202-215
Author(s):  
Ranti Dwi Djayanti ◽  
Yani Iriani
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Distribution System ◽  
Transportation Cost ◽  
Transportation Costs ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Total Distance ◽  
Ant Behavior ◽  
Total Transportation Cost

PT XYZ is one of freight forwarding companies in Indonesia, which is located in the city of Bandung. This company has managerial functions related to Collecting, Processing, Transporting, Delivery, and Reporting. However, the fact is in the process of Transporting this company still uses a zoning system which is a shipping system that still divides tertiary areas and each of these areas uses one vehicle. One problem that arises is that companies want effective and efficient performance in the distribution system of goods with the minimum total transportation costs. However, the company does not know yet whether the company's shipping routes have been effective and efficient or not. The company has tertiary network distribution route that are 2 routes with a total distance of 143.4 Km and a total transportation cost of  Rp 5,681,484 /month. This research aims to determine the optimal goods distribution route using the Ant Colony Optimization Algorithm method, which is the method of finding the shortest path following ant behavior in taking food to its nest. Based on the results of the research, it is obtained a total distance of 109.2 Km because it becomes 1 route and total transportation costs Rp 3,337,992 /month, then it is obtained optimal results with a difference in distance is 34.2 Km and a total transportation cost of  Rp 2,343,492 /month using one vehicle. Keywords: Optimization, Distribution, Ant Colony Optimization Algorithm    

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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