Dynamic routing,modulation level and spectrum allocation (RMLSA) in FWDM with modulation format conversion

This paper proposes a dynamic routing, modulation level and spectrum allocation (RMLSA) scheme in the flexible optical wavelength-division multiplexing (FWDM) networks with modulation format conversion ability. The scheme considers the modulation format conversion at the intermediate nodes and addresses the fragmentation problem by avoiding appearance of them. The influence of routing to the emergence of the fragmentation is quantified, which is referenced to decide which one route of k-paths to use. Simulation results demonstrate efficient reductions in blocking rates and improvements in failure recovery rates for the scheme in the network.     

The Arc-Item-Load and Related Formulations for the Cumulative Vehicle Routing Problem

The Capacitated Vehicle Routing Problem (CVRP) consists of finding the cheapest way to serve a set of customers with a fleet of vehicles of a given capacity. While serving a particular customer, each vehicle picks up its demand and carries its weight throughout the rest of its route. While costs in the classical CVRP are measured in terms of a given arc distance, the Cumulative Vehicle Routing Problem (CmVRP) is a variant of the problem that aims to minimize total energy consumption. Each arc’s energy consumption is defined as the product of the arc distance by the weight accumulated since the beginning of the route.The purpose of this work is to propose several different formulations for the CmVRP and to study their Linear Programming (LP) relaxations. In particular, the goal is to study formulations based on combining an arc-item concept (that keeps track of whether a given customer has already been visited when traversing a specific arc) with another formulation from the recent literature, the Arc-Load formulation (that determines how much load goes through an arc).Both formulations have been studied independently before – the Arc-Item is very similar to a multi-commodity-flow formulation in Letchford and Salazar-González (2015) and the Arc-Load formulation has been studied in Fukasawa et al. (2016) – and their LP relaxations are incomparable. Nonetheless, we show that a formulation combining the two (called Arc-Item-Load) may lead to a significantly stronger LP relaxation, thereby indicating that the two formulations capture complementary aspects of the problem. In addition, we study how set partitioning based formulations can be combined with these formulations. We present computational experiments on several well-known benchmark instances that highlight the advantages and drawbacks of the LP relaxation of each formulation and point to potential avenues of future research.     

An iterated local search algorithm for the single-vehicle cyclic inventory routing problem

The Single-Vehicle Cyclic Inventory Routing Problem (SV-CIRP) belongs to the class of Inventory Routing Problems (IRP) in which the supplier optimises both the distribution costs and the inventory costs at the customers. The goal of the SV-CIRP is to minimise both kinds of costs and to maximise the collected rewards, by selecting a subset of customers from a given set and determining the quantity to be delivered to each customer and the vehicle routes, while avoiding stockouts. A cyclic distribution plan should be developed for a single vehicle.     

A multi-period TSP with stochastic regular and urgent demands

In this paper, we study the multi-period TSP problem with stochastic urgent and regular demands. Urgent demands have to be satisfied immediately while regular demands can be satisfied either immediately or the day after. Demands appear stochastically at nodes. The objective is to minimize the average long-run delivery costs, knowing the probabilities governing the demands at nodes.     

Integrated optimization of customer and supplier logistics at Robert Bosch LLC

Large automotive supply chains typically involve manufacturers pulling materials from their suppliers along the chain, usually by using round-trip truckload routes. The return trips on these routes are used to return empty containers back to the suppliers. The mismatch between the amount of materials and empty containers results in underutilization of the return trips. A supplier can utilize this unused capacity by identifying a subset of promising customer routes that can be combined with its existing supplier routes to save overall costs of the system. Such an integration also leads to other supply chain coordination benefits such as the potential of using crossdocks, more frequent milkruns and ensuing reductions in inventories.     

Optimization of transit route network,vehicle headways and timetables for large-scale transit networks

This paper presents a metaheuristic method for optimizing transit networks, including route network design, vehicle headway, and timetable assignment. Given information on transit demand, the street network of the transit service area, and total fleet size, the goal is to identify a transit network that minimizes a passenger cost function. Transit network optimization is a complex combinatorial problem due to huge search spaces of route network, vehicle headways, and timetables. The methodology described in this paper includes a representation of transit network variable search spaces (route network, headway, and timetable); a user cost function based on passenger random arrival times, route network, vehicle headways, and timetables; and a metaheuristic search scheme that combines simulated annealing, tabu, and greedy search methods. This methodology has been tested with problems reported in the existing literature, and applied to a large-scale realistic network optimization problem. The results show that the methodology is capable of producing improved solutions to large-scale transit network design problems in reasonable amounts of time and computing resources.     

The effects of triangle inequality on the vehicle routing problem

Routing problems often utilize experimental networks to represent real world scenarios. However most ignore the inclusion of triangle inequality violations, a phenomenon resulting from delays or rounding errors within a network. This work evaluates the effect of both frequency – the number of violations – and severity – the degree of intensity of a violation – of triangle inequality and evaluates both solution quality and solution time based on Simulated Annealing, Ant Colony Optimization and Savings Algorithm methods. Findings indicate that while both frequency and severity degrade solution quality, increased levels of frequency and severity together result in significant adverse affects to solution quality. Solution time, however, is not impacted by the presence of triangle inequality violations within the network. This information should encourage practitioners to identify delays and maintain the presence of triangle inequality violations in a network to ensure accuracy of solution quality.     

Vehicle routing with soft time windows and stochastic travel times: A column generation and branch-and-price solution approach

We study a vehicle routing problem with soft time windows and stochastic travel times. In this problem, we consider stochastic travel times to obtain routes which are both efficient and reliable. In our problem setting, soft time windows allow early and late servicing at customers by incurring some penalty costs. The objective is to minimize the sum of transportation costs and service costs. Transportation costs result from three elements which are the total distance traveled, the number of vehicles used and the total expected overtime of the drivers. Service costs are incurred for early and late arrivals; these correspond to time-window violations at the customers. We apply a column generation procedure to solve this problem. The master problem can be modeled as a classical set partitioning problem. The pricing subproblem, for each vehicle, corresponds to an elementary shortest path problem with resource constraints. To generate an integer solution, we embed our column generation procedure within a branch-and-price method. Computational results obtained by experimenting with well-known problem instances are reported.