The Vehicle Routing Problem with Service Level Constraints

We consider a vehicle routing problem which seeks to minimize cost subject to service level constraints on several groups of deliveries. This problem captures some essential challenges faced by a logistics provider which operates transportation services for a limited number of partners and should respect contractual obligations on service levels. The problem also generalizes several important classes of vehicle routing problems with profits. To solve it, we propose a compact mathematical formulation, a branch-and-price algorithm, and a hybrid genetic algorithm with population management, which relies on problem-tailored solution representation, crossover and local search operators, as well as an adaptive penalization mechanism establishing a good balance between service levels and costs. Our computational experiments show that the proposed heuristic returns very high-quality solutions for this difficult problem, matches all optimal solutions found for small and medium-scale benchmark instances, and improves upon existing algorithms for two important special cases: the vehicle routing problem with private fleet and common carrier, and the capacitated profitable tour problem. The branch-and-price algorithm also produces new optimal solutions for all three problems

Demand and routing models for urban goods movement simulation

This paper presents a macro-architecture for simulating goods movements in an urban area. Urban goods supply is analysed when the retailer is the decision-maker and chooses to supply his/her shop. Two components are considered: demand in terms of goods supply and vehicle routing with constraints to simulate goods movements. To analyse demand we consider a multi-step model, while to analyse goods movements a Vehicle Routing Problem with Time Windows (VRPTW) is formalized. We examine the distribution process for a VRPTW in which the optimum paths between all the customers are combined to determine the best vehicle trip chain. As regard optimum path search, a multipath approach is proposed that entails the generation of more than one path between two delivery points. Some procedures (traffic assignment, real time system measurement, reverse assignment) to estimate system performance are also proposed. Finally, heuristics to solve the proposed problem are reported and their results are compared with those exact

An auction for collaborative vehicle routing: Models and algorithms

Increasing competition and expectations from customers pressures carriers to further improve efficiency. Forming collaborations is essential for carriers to reach their targeted efficiency levels. In this study, we investigate an auction mechanism to facilitate collaboration amongst carriers while maintaining autonomy for the individual carriers. Multiple auction implementations are evaluated. As the underlying decision problem (which is a traditional vehicle routing problem) is known to be NP-hard, this auction mechanism has an important inherent complexity. Therefore, we use fast and efficient algorithms for the vehicle routing problem to ensure that the auction can be used in operational decision making. Numerical results are presented, indicating that the auction achieves a savings potential better than the thus far reported approaches in the literature. Managerial insights are discussed, particularly related to the properties of the auction and value of the information

Design and Control of Warehouse Order Picking: a literature review

Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.Order picking;Logistics;Warehouse Management

A GA-based simulation system for WMNs: comparison analysis for different number of flows, client distributions, DCF and EDCA functions

In this paper, we compare the performance of Distributed Coordination Function (DCF) and Enhanced Distributed Channel Access (EDCA) for normal and uniform distributions of mesh clients considering two Wireless Mesh Network (WMN) architectures. As evaluation metrics, we consider throughput, delay, jitter and fairness index metrics. For simulations, we used WMN-GA simulation system, ns-3 and Optimized Link State Routing. The simulation results show that for normal distribution, the throughput of I/B WMN is higher than Hybrid WMN architecture. For uniform distribution, in case of I/B WMN, the throughput of EDCA is a little bit higher than Hybrid WMN. However, for Hybrid WMN, the throughput of DCF is higher than EDCA. For normal distribution, the delay and jitter of Hybrid WMN are lower compared with I/B WMN. For uniform distribution, the delay and jitter of both architectures are almost the same. However, in the case of DCF for 20 flows, the delay and jitter of I/B WMN are lower compared with Hybrid WMN. For I/B architecture, in case of normal distribution the fairness index of DCF is higher than EDCA. However, for Hybrid WMN, the fairness index of EDCA is higher than DCF. For uniform distribution, the fairness index of few flows is higher than others for both WMN architectures.Peer ReviewedPostprint (author's final draft

Energy Efficient QoS Routing Protocol based on Genetic Algorithm in MANET

Abstract- In mobile ad-hoc networks (MANETs), providing quality of service is more challenging than wired networks, because of multi hop communication, node connectivity and lack of central co-ordination. Mobile ad-hoc networks need sure distinctive characteristics which might cause difficulties providing QoS in such network. Coming up with of multi constrained QoS routing protocols remains troublesome. As a result of routing protocols must satisfy the numerous QoS metrics at a time. Genetic algorithm based routing protocol will give the solution for multi constrained QoS routing problem. In existing genetic algorithm based routing, achieving energy efficiency is the major drawback. To overcome this drawback, in this paper, we have proposed genetic algorithm based energy efficient QoS routing for MANET. Proposed GA based routing algorithm discovered the shortest path from source to destination, which can consumes less energy compare to existing algorithms. In this paper TCP,CBR and video sources are applied at a time then energy consumption of proposed algorithm is compared with existing normal GA based and AOMDV. Simulation results show that proposed algorithm consumes less energy towards given scenario. Simulations are performed in NS-2