An application of Special Ordered Sets to a periodic milk collection problem

We present an OR-based approach to support a milk collection problem in a special branch of dairy industry. The annual growth of the sector and the continuous imbalance between milk supply and demand, has urged the sector to look for a different approach to their daily milk collection problem. Specific details of the problem environment (i.e., the continuous production on supply level and the delivery conditions on demand level) gave rise to choose for a short- to medium-term planning approach. The proposed decision support system has to be considered as an efficient tool for generating stable milk collection plans which in turn also serves as an effective starting point for the vehicle routing problem. From a computational point of view it turned out that the application of Special Ordered Sets type 1 (SOS1) was very useful. Although it appears from literature that the computational advantage of SOS1 is restricted to supplementary model conditions, this study shows that these conditions are not necessarily needed.     

集货送货一体化的物流配送车辆路线问题的标号算法

本文结合实际情况,对具有时间窗约束的集货送货一体化的车辆路线问题进行了研究,针对该问题的特点,采用修正的多属性标号算法对该问题进行求解,并通过C 编程语言实现了该算法,最后用一个示例表明本文的算法是有效的.     

Uniqueness of the solution for optimal static routing in open BCMP queueing networks

Optimal static routing problems in open BCMP queueing networks with state-independent arrival and service rates are studied. They include static routing problems in communication networks and optimal static load balancing problems in distributed computer systems. We consider an overall optimal policy that is the routing policy whereby the overall mean response (or sojourn) time of a job is minimized. We obtain the routing decisions of the overall optimal policy and show that they may not be unique, but that the utilization of each service center is uniquely determined by the overall optimal policy. We also consider an individually optimal policy whereby jobs are routed so that each job may feel that its own expected response time is minimized if it knows the mean delay time for each path.     

车辆路径问题的混合优化算法

讨论了一类车辆路径调度问题(VRP)及其数学模型，并且分析了以遗传算法求解该类问题时的染色体表示和有关遗传操作，然后结合2-opt局部优化算法提出了GA with2-opt算法来求解VRP问题，试验结果说明了该算法的有效性和可行性。     

A flexible adaptive memory-based algorithm for real-life transportation operations: Two case studies from dairy and construction sector

Effective routing of vehicles remains a focal goal of all modern enterprises, thriving for excellence in project management with minimal investment and operational costs. This paper proposes a metaheuristic methodology for solving a practical variant of the well-known Vehicle Routing Problem, called Heterogeneous Fixed Fleet VRP (HFFVRP). Using a two-phase construction heuristic, called GEneralized ROute Construction Algorithm (GEROCA), the proposed metaheuristic approach enhances its flexibility to easily adopt various operational constraints. Via this approach, two real-life distribution problems faced by a dairy and a construction company were tackled and formulated as HFFVRP. Computational results on the aforementioned case studies show that the proposed metaheuristic approach (a) consistently outperforms previous published metaheuristic approaches we have developed to solve the HFFVRP, and (b) substantially improves upon the current practice of the company. The key result that impressed both companies’ management was the improvement over the bi-objective character of their problems: the minimization of the total distribution cost as well as the minimization of the number of the given heterogeneous number of vehicles used.     

Formulations and Valid Inequalities for the Heterogeneous Vehicle Routing Problem

We consider the vehicle routing problem where one can choose among vehicles with different costs and capacities to serve the trips. We develop six different formulations: the first four based on Miller-Tucker-Zemlin constraints and the last two based on flows. We compare the linear programming bounds of these formulations. We derive valid inequalities and lift some of the constraints to improve the lower bounds. We generalize and strengthen subtour elimination and generalized large multistar inequalities.     

Optimizing garbage collection vehicle routing problem with alternative fuel-powered vehicles

Abstract

This paper considers the garbage collection problem in which vehicles with multiple compartments are used to collect the garbage. The vehicles are considered to be Alternative Fuel-powered Vehicles (AFVs). Compared with the traditional fossil fuel powered vehicles, the AFVs have limited fuel tank capacity. In addition, AFVs are allowed to refuel only at the depot. We provide a mathematical formulation and develop two solution approaches to solve the problem. The first approach is based on the saving algorithm, while the second is based on the ant colony system (ACS) metaheuristic. New problem instances have been generated to evaluate the performance of the proposed algorithms.     

基于特殊路径的局内车辆路径问题混合策略研究

针对运输途中遇到的某一或一系列无法预知的堵塞事件对决策者路径选择策略的影响,考虑堵塞只发生在一条特殊路径上且可恢复的情况,采用局内竞争分析的思想,建立了局内车辆路径问题的数学模型,对车辆到达堵塞点时堵塞恢复时间未知这一情形下的路径选择问题,提出了两种混合策略,给出了相应的竞争比,并对其竞争性能进行了理论分析。     

Column generation for vehicle routing problems with multiple synchronization constraints

Synchronization of workers and vehicles plays a major role in many industries such as logistics, healthcare or airport ground handling. In this paper, we focus on operational ground handling planning and model it as an archetype of vehicle routing problems with multiple synchronization constraints, coined as “abstract vehicle routing problem with worker and vehicle synchronization” (AVRPWVS). The AVRPWVS deals with routing workers to ground handling jobs such as unloading baggage or refuelling an aircraft, while meeting each job’s time window. Moreover, each job can be performed by a variable number of workers. As airports span vast distances and due to security regulations, workers use vehicles to travel between locations. Furthermore, each vehicle, moved by a driver, can carry several workers. We propose two mathematical multi-commodity flow formulations based on time-space networks to efficiently model five synchronization types including movement and load synchronization. Moreover, we develop a branch-and-price heuristic that employs both conventional variable branching and a novel variable fixing strategy. We demonstrate that the procedure achieves results close to the optimal solution in short time when compared to the two integer models.