Search for optimal routes on roads applying metaheuristic algorithms

The design of efficient routes for vehicles visiting a significant number of destinations is a critical factor for the competitiveness of many companies. The design of such routes is known as the vehicle routing problem. Indeed, efficient vehicle routing is one of the most studied problems in the areas of logistics and combinatorial optimization. The present study presents a memetic algorithm that evolves using a mechanism inspired by virus mutations. Additionally, the algorithm uses Taboo Search as an intensification mechanism

Joint Route Planning under Varying Market Conditions

Purpose - To provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics.Design/methodology/approach - Joint route planning is a measure that companies can take to decrease the costs of their distribution activities. Essentially, this can either be achieved through horizontal cooperation or through outsourcing distribution to a Logistics Service Provider.The synergy value is defined as the difference between distribution costs in the original situation where all entities perform their orders individually, and the costs of a system where all orders are collected and route schemes are set up simultaneously to exploit economies of scale.This paper provides estimates of synergy values, both in a constructed benchmark case and in a number of real-world cases.Findings - It turns out that synergy values of 30% are achievable.Furthermore, intuition is developed on how the synergy values depend on characteristics of the distribution problem under consideration.Practical implications - The developed intuition on the nature of synergy values can help practitioners to find suitable combinations of distribution systems, since synergy values can quickly be assessed based on the characteristics of the distribution problem, without solving large and difficult Vehicle Routing Problems.Originality/value - this paper addresses a major impediment to horizontal cooperation: estimating operational savings upfront.Horizontal cooperation;Distribution;Outsourcing;Vehicle routing with time windows;Retail

Design and optimisation of a low cost Cognitive Mesh Network

Wireless Mesh Networks (WMNs) have been touted as the most promising wireless technology in providing high-bandwidth Internet access to rural, remote and under-served areas, with relatively lower investment cost as compared to traditional access networks. WMNs structurally comprise of mesh routers and mesh clients. Furthermore, WMNs have an envisaged ability to provide a heterogeneous network system that integrates wireless technologies such as IEEE 802.22 WRAN, IEEE 802.16 WiMAX, IEEE 802.11 Wi-Fi, Blue-tooth etc. The recent proliferation of new devices on the market such as smart phones and, tablets, and the growing number of resource hungry applications has placed a serious strain on spectrum availability which gives rise to the spectrum scarcity problem. The spectrum scarcity problem essentially results in increased spectrum prices that hamper the growth and efficient performance of WMNs as well as subsequent transformation of WMN into the envisaged next generation networks. Recent developments in TV white space communications technology and the emergence of Cognitive radio devices that facilitate Dynamic Spectrum Access (DSA) have provided an opportunity to mitigate the spectrum scarcity problem. To solve the scarcity problem, this thesis reconsiders the classical Network Engineering (NE) and Traffic Engineering (TE) problems to objectively design a low cost Cognitive Mesh network that promotes efficient resources utilization and thereby achieve better Quality of Service (QoS) levels

An Improved Excitation Matching Method based on an Ant Colony Optimization for Suboptimal-Free Clustering in Sum-Difference Compromise Synthesis

Dealing with an excitation matching method, this paper presents a global optimization strategy for the optimal clustering in sum-difference compromise linear arrays. Starting from a combinatorial formulation of the problem at hand, the proposed technique is aimed at determining the sub-array configuration expressed as the optimal path inside a directed acyclic graph structure modelling the solution space. Towards this end, an ant colony metaheuristic is used to benefit of its hill-climbing properties in dealing with the non-convexity of the sub-arraying as well as in managing graph searches. A selected set of numerical experiments are reported to assess the efficiency and current limitations of the ant-based strategy also in comparison with previous local combinatorial search methods. (c) 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

A Polyhedral Study of Mixed 0-1 Set

We consider a variant of the well-known single node fixed charge network flow set with constant capacities. This set arises from the relaxation of more general mixed integer sets such as lot-sizing problems with multiple suppliers. We provide a complete polyhedral characterization of the convex hull of the given set

Preliminary evaluation for road network improvement alternatives in less developed countries.

Thesis. 1975. M.S.--Massachusetts Institute of Technology. Dept. of Civil Engineering.Includes bibliographical references.M.S

Multi-vehicle Dispatching And Routing With Time Window Constraints And Limited Dock Capacity

The Vehicle Routing Problem with Time Windows (VRPTW) is an important and computationally hard optimization problem frequently encountered in Scheduling and logistics. The Vehicle Routing Problem (VRP) can be described as the problem of designing the most efficient and economical routes from one depot to a set of customers using a limited number of vehicles. This research addresses the VRPTW under the following additional complicating features that are often encountered in practical problems: 1. Customers have strict time windows for receiving a vehicle, i.e., vehicles are not allowed to arrive at the customer’s location earlier than the lower limit of the specified time window, which is relaxed in previous research work. 2. There is a limited number of loading/unloading docks for dispatching/receiving the vehicles at the depot The main goal of this research is to propose a framework for solving the VRPTW with the constraints stated above by generating near-optimal routes for the vehicles so as to minimize the total traveling distance. First, the proposed framework clusters customers into groups based on their proximity to each other. Second, a Probabilistic Route Generation (PRG) algorithm is applied to each cluster to find the best route for visiting customers by each vehicle; multiple routes per vehicle are generated and each route is associated with a set of feasible dispatching times from the depot. Third, an assignment problem formulation determines the best dispatching time and route for each vehicle that minimizes the total traveling distance. iii The proposed algorithm is tested on a set of benchmark problems that were originally developed by Marius M. Solomon and the results indicate that the algorithm works well with about 1.14% average deviation from the best-known solutions. The benchmark problems are then modified by adjusting some of the customer time window limits, and adding the staggered vehicle dispatching constraint. For demonstration purposes, the proposed clustering and PRG algorithms are then applied to the modified benchmark problems

Computer programs for shielding problems in manned space vehicles

Computer programs for shielding problems in manned space vehicles - proton penetration code

Models and advanced optimization algorithms for the integrated management of logistics operations

Tese de Doutoramento em Engenharia Industrial e de Sistemas.In this thesis, we propose a set of algorithms regarding real combinatorial optimization problems in the context of transportation of goods. These problems consist in the combination of the vehicle routing problem with the two-dimensional bin-packing problem, which is also known as the vehicle routing problem with two-dimensional loading constraints. We also analyzed two related problems, namely the elementary shortest path and the vehicle routing problem with mixed linehauls and backhauls. In both problems, two-dimensional loading constraints are explicitly considered. Two column generation based approaches are proposed for the vehicle routing problem with two-dimensional constraints. The rst one relies on a branch-and-price algorithm with di erent branching schemes. A family of dual valid inequalities is also de ned, aiming to accelerate the convergence of the algorithm. The second approach is based on a set of di erent heuristics strategies, which are applied to the reformulated model. The elementary shortest path problem with two-dimensional constraints is addressed due to its importance in solving the subproblem of the column generation algorithms. To the best of our knowledge, we contribute with the rst approach for this problem, through di erent constructive strategies to achieve feasible solutions, and a variable neighborhood search algorithm in order to search for improved solutions. In what concerns the vehicle routing problem with mixed linehaul and backhauls and two-dimensional loading constraints, di erent variable neighborhood search algorithms are proposed. These algorithms explored various neighborhood structures, being some of those developed based on the features of the problem. All the proposed methods were implemented and experimentally tested. An exhaustive set of computational tests was conducted, using, for this purpose, a large group of benchmark instances. In some cases, a large set of benchmark instances was adapted in order asses the quality of the proposed models. All the obtained results are presented and discussed.Nesta tese, propomos um conjunto de algoritmos sobre problemas reais de otimiza c~ao combinat oria no contexto do transporte de bens. Estes problemas consistem na combina c~ao do problema de planeamento de rotas de ve culos com o problema de empacotamento bidimensional, que tamb em e conhecido como o problema de planeamento de rotas de ve culos com restri c~oes de carregamento bidimensional. Analisamos tamb em dois problemas relacionados, nomeadamente o problema de caminho mais curto e o problema de planeamento de rotas ve culos com entregas e recolhas indiferenciadas. Em ambos os problemas, s~ao explicitamente consideradas restri c~oes de carregamento bidimensional. Duas abordagens baseadas em gera c~ao de colunas s~ao propostas para o problema de planeamento de rotas de ve culos com restri c~oes de carregamento bidimensional. O primeiro baseia-se num algoritmo de parti c~ao e gera c~ao de colunas com diferentes estrat egias de parti c~ao. Uma fam lia de desigualdades duais v alidas e tamb em apresentada, com o objetivo de acelerar a converg^encia do algoritmo. A segunda abordagem baseia-se num conjunto de diferentes estrat egias heur sticas, que s~ao aplicadas ao modelo reformulado. O problema do caminho mais curto com restri c~oes de carregamento bidimensional e abordado devido a sua import^ancia na resolu c~ao do subproblema dos aos algoritmos de gera c~ao de colunas. De acordo com o nosso conhecimento, contribu mos com a primeira abordagem para este problema, atrav es de diferentes estrat egias construtivas para obter solu c~oes v alidas, e um algoritmo de pesquisa em vizinhan ca vari avel, com o objetivo de encontrar solu c~oes de melhor qualidade. No que concerne ao problema de planeamento de rotas de ve culos com entregas e recolhas indiferenciadas, diferentes algoritmos de pesquisa em vizinhan ca vari avel s~ao propostos. Estes algoritmos exploram v arias estruturas de vizinhan ca, sendo algumas destas desenvolvidas com base nas caracter sticas do problema. Todos os m etodos propostos foram implementados e testados experimentalmente. Um extenso conjunto de testes computacionais foi efetuado, utilizando um grande grupo de inst^ancias descritas na literatura. Em alguns casos, um grande conjunto de inst^ancias descritas na literatura foi adaptado com o objetivo de avaliar a qualidade dos m etodos propostos