A Solution for Transportation Planning in Supply Chain (original) (raw)
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Development of an integrated system for distribution planning in supply chain
South African Journal of Business Management
Distribution planning, which includes Vehicle Routing and Scheduling Problem (VRSP), has become an important element in Supply Chain impacting its service level and efficiency. Computer Aided Routing and Scheduling (CARS) has been developed and implemented, which can handle complicated distribution models using advanced heuristic optimization algorithms. A classification scheme is introduced to classify various types of routing and scheduling problems in a structured manner, based on the main objects of VRSP. The integrated system described in this paper can manage the dynamic aspects of the Supply Chain in practice. The modelling and solution approach in the CARS optimization engine, its user interface, sample performance measurements, and planning and operational features of the system are described in detail.
2015
Vehicle Routing Problem (VRP) is one of the most challenging problems in combinatorial optimization. Objective of VRP is to find minimum length route starts and ends in a depot. There are some additional constraints such as more than one depot, service time, time window, capacity of vehicle, and many more. These are cause of VRP variants. Vehicle Routing Problem with Time Windows (VRPTW) is a variant of VRP with some additional constrains, that are number of requests may not exceed the vehicle capacity, as well as travel time and service time may not exceed the time window. Multi Depot Vehicle Routing Problem (MDVRP) has number of depots serving all customers, a number of vehicles distributing goods to customers with a minimum distance of distribution route without exceeding the capacity of the vehicle. Many researches have presented algorithms to solve VRPTW and MDVRP. This article discusses solution characteristics of VRPTW and MDVRP algorithms, and their performance. VRPTW algori...
Optimal Routing in Supply Chain Aimed at Minimizing Vehicle Cost and Supply
Transportation plays a vital role in supply chain. An inefficient transportation system disrupts supply chain and imposes severe damages to it. This paper investigates a transportation model with a limited number of vehicles with different capacities. The vehicles are used to handle raw and semi-finished materials from contractors' warehouses to the main factories and to transport finished products to the warehouses of the distribution companies. The main purpose was to cover all transportation requests in a manner that it results in a reduced transportation cost, a reduced use of rental vehicles, and a reduced stopping duration of vehicle in destinations through the optimal use of available resources. In the considered model, first, a web-based system was designed in order to enable the registration of handling requests in the system with the purpose of compensating vehicle shortage. The handling requests are confirmed by drivers and transportation companies through SMS, email, and internet. Then, the proposed model performs network routing in order to completely cover the transportation network and to reduce transportation costs and vehicles stopping duration in destination. Finally, the model was run in different conditions, and the possibility of increasing vehicles with the purpose of reducing costs was studied.
IOP Conference Series: Materials Science and Engineering, 2017
XYZ is a distributor of various consumer goods products. The company plans its delivery routes daily and in order to obtain route construction in a short amount of time, it simplifies the process by assigning drivers based on geographic regions. This approach results in inefficient use of vehicles leading to imbalance workloads. In this paper, we propose a combined method involving heuristic and optimization to obtain better solutions in acceptable computation time. The heuristic is based on a time-oriented, nearest neighbor (TONN) to form clusters if the number of locations is higher than a certain value. The optimization part uses a mathematical modeling formulation based on vehicle routing problem that considers heterogeneous vehicles, time windows, and fixed costs (HVRPTWF) and is used to solve routing problem in clusters. A case study using data from one month of the company's operations is analyzed, and data from one day of operations are detailed in this paper. The analysis shows that the proposed method results in 24% cost savings on that month, but it can be as high as 54% in a day.
Models and Algorihtm for the Optimization of Real-World Routing and Logistics Problems
2015
Logistics involves planning, managing, and organizing the flows of goods from the point of origin to the point of destination in order to meet some requirements. Logistics and transportation aspects are very important and represent a relevant costs for producing and shipping companies, but also for public administration and private citizens. The optimization of resources and the improvement in the organization of operations is crucial for all branches of logistics, from the operation management to the transportation. As we will have the chance to see in this work, optimization techniques, models, and algorithms represent important methods to solve the always new and more complex problems arising in different segments of logistics. Many operation management and transportation problems are related to the optimization class of problems called Vehicle Routing Problems (VRPs). In this work, we consider several real-world deterministic and stochastic problems that are included in the wide...
A Modelling and Optimization Framework for Real-World Vehicle Routing Problems
Vehicle Routing …, 2008
The globalisation of the economy leads to a rapidly growing exchange of goods on our planet. Limited commodities and transportation resources, high planning complexity and the increasing cost pressure through the strong competition between logistics service providers make it essential to use computer-aided systems for the planning of the transports. An important subtask in this context is the operational planning of trucks or other specialized transportation vehicles. These optimization tasks are called Vehicle Routing Problems (VRP). Over 1000 papers about a huge variety of Vehicle Routing Problems indicate the practical and theoretical importance of this NP-hard optimization problem. Therefore, many specific solvers for different Vehicle Routing Problems can be found in the literature. The drawback is that most of these solvers are high specialized and inflexible and it needs a lot of effort to adapt them to modified problems. Additionally, most real world problems are often much more complex than the idealized problems out of literature and they also change over time. To face this issue, we present an integrated modelling and optimization framework for solving complex and practical relevant Vehicle Routing Problems. The modular structure of the framework, a script based modelling language, a library of VRP related algorithms and a graphical user interface give the user both reusable components and high flexibility for rapid prototyping of complex Vehicle Routing Problems.
Vehicle Routing, Scheduling and Decision Utility Environment
Advances in Social Sciences Research Journal
There have been many papers written in literature in vehicle scheduling. In this paper, we will try to summarize all previous research papers in this area. In this section of the paper we basically deal with Vehicle Scheduling and Routing. We assume a given system for Distribution System replenishment and given set of Distribution Centers ask ourselves how should Vehicles be scheduled or routed to achieve the company's logistic objectives? The problem as typically formulated is to determine the order turn in which the customers will be visited by delivery or pickup vehicles otherwise called the route.
Implementing vehicle routing models
Transportation Research Part B: Methodological, 1990
This paper shows how idealized models can be used to obtain cost-effective, implementable solutions to large and complex logistics problems. It advocates the use of fine tuning software to translate the guidelines produced by idealized models into specific feasible solutions. The "traveling salesman" (TSP) and "vehicle routing" (VHP) problems were used to test the approach. For sufficiently large problems the proposed procedure leads to solutions that improve on those produced by either idealized models or numerical methods alone. Simulated annealing (SA) was chosen for fine tuning. This optimization procedure is ideally suited for this purpose because of its general applicability, and as the research demonstrates, a prototype software package can be quickly produced. The experiments also revealed that the TSP and VRP tour lengths predicted by the idealized models are close (surprisingly so in some cases) to those of actual tours.
Advanced vehicle routing algorithms for complex operations management problems
Journal of Food Engineering, 2005
Vehicle routing encompasses a whole class of complex optimization problems that target the derivation of minimum total cost routes for a number of resources (vehicles) located at a central point (depot) in order to service efficiently a number of demand points (customers). Several practical issues in the food industry, involving both production and transportation decisions are modelled as VRP instances and are hard combinatorial problems in the strong sense (NP-hard). For such problems, metaheuristics, i.e., general solution procedures that explore the solution space to identify high quality solutions and often embed some standard route construction and improvement algorithms have been proposed. This paper surveys the recent research efforts on metaheuristic solution methodologies for the standard and most widely studied version of the Vehicle Routing Problem (VRP), i.e., the Capacitated VRP. The computational performance of each metaheuristic is presented for the 14 benchmark instances of Christofides et al.