Wireless sensors have been used for monitoring and tracking in several areas. With regard to their use in smart cities, these can be used to improve traffic control in large cities [13,14], collect information of passenger volume , provide optimal routes in real time , to reduce greenhouse gas (GHG) emissions , in rescue scenarios after a disaster  and even to aid the blind . In , the system used for data gathering is discussed, but no further planning using such information is done. Our work on vehiclerouting with backup provisioning goes further and uses the gathered data for vehicle route planning. The problem addressed in  is different from ours and can be considered more like a dynamic vehiclerouting problem (DVRP), which has a wide range of real-world applications, as stated in . In DVRP, real-time communication between vehicles and planners is required, and adjustments of the optimized routes can be performed during the execution process. This kind of problem, however, is not adequate when stops must be previously defined, which is the case that we are studying. The problem addressed in  falls into the category of green vehiclerouting problems (GVRP), and the objective is to find routes while minimizing GHG emissions. In rescue scenarios, considered in , the demand-related information is quite limited in the initial rescue period and is intuitively unpredictable using historical data, and the emergency resources may be insufficient. The problems addressed in [17,18] are, therefore, different from the one considered in this article.
Dentre as várias classes do VehicleRouting Problem (VRP), a que se mostra mais adequada a este problema é o Open VehicleRouting Problem (OVRP), que difere do VRP pelo fato de os veículos não retornarem ao depósito (nesse caso a garagem) após atenderem o último cliente. Entre os estudos já realizados sobre o OVRP, o trabalho de Bektas e Elmastas (2007) é o que mais se assemelha ao problema de transporte de empregados por uma frota de ônibus fretada, porém, ele foi aplicado ao problema de transporte escolar. Desta forma, utilizou-se o modelo proposto por estes auto- res com o intuito de reduzir o custo total de transporte de empregados por meio de uma frota de ônibus fretada. O mo- delo proposto difere do modelo de Bektas e Elmastas (2007) pelo fato de introduzir limites inferiores e superiores para o número de ônibus utilizados no transporte.
Concerning oil exploitation, there is a class of onshore wells called artiﬁcial lift wells where the use of auxiliary methods for the elevation of ﬂuids (oil and water) is necessary. In this case, a ﬁxed system of beam pump is used when the well has a high productivity. Because oil is not a renewable product, the production of such wells will diminish until the utilization of equipment permanently allocated to them will become economically unfeasible. The exploitation of low productivity wells can be done by mobile equipment coupled to a truck. This vehicle has to perform daily tours visiting wells, starting and ﬁnishing at the oil treatment station (OTS), where separation of oil from water occurs. Usually the mobile collector is not able to visit all wells in a single day. In this context, arises the problem called oil collecting vehiclerouting problem (OCVRP). In this problem, the objective is to collect the maximum amount of oil in a single day, starting and
This work presented the vehiclerouting optimization system developed to be integrated with an existing ERP. The optimization procedure takes into consideration the need for a near real-time routing solution under dynamic orders and interactions with the system administrator. In this sight, this work described the interactions and dependencies between the system’s four main components, namely: i3FR-Opt (where the computation of the routes is done), the i3FR-Hub (implementing a channel to all the communications inside the system and to the exterior), the i3FR-DB (provider of local storage to the information relevant to the optimization procedure), and i3FR-Maps (a cartography subsystem of routing informations). With this structure it is possible to deal with late orders and diﬀerent states for the routes, which allows to do a phased picking and loading of the vehicles. As mere examples, some results for the Algarve’s region were presented showing diﬀerent solution depending on the time windows restrictions.
Several approaches have been proposed to address variants of the problem tackled in this thesis. Our contribution is two-fold. Firstly, to the best of our knowledge, there is no work that tackles the service level agreement often encountered in these logistics systems, in which not only the delivery window, but also the time between ordering and receiving in the same day is defined. This constraint limits drastically the number of clients to be paired and the flexibility in the departure times of the vehicles. Secondly, although several formulations have been put forward to solve consistent vehiclerouting problems, they were never used to address real-world instances. In this work we propose a solution method leveraged by a fix-and-optimize approach that fully utilizes the developed mathematical model and aims to be well suited for application in real-life business situations. In order to test its validity and potential, the solution method is used with historical data to plan the robust routes of a Portuguese pharmaceutical distribution company with over 3000 daily deliveries in an environment with both deterministic and stochastic customers and stochastic demand. The proposed plans are then simulated and the performance of the new plan is compared to the one currently in practice at the company.
One of the most important extensions of the CVRP is the VehicleRouting Problem with Time Window (VRPTW) which is each customer must be served within a specific time window. The objective is to minimize the vehicle fleet with the sum of travel time and waiting time needed to supply all customers in their required hour , . A variety of exact algorithms and efficient heuristics have already been proposed for VRPTW by many researchers as shown in Table 1. In addition, Table 2 represents the various methods applying in exact algorithm, classical heuristic algorithms and metaheuristic algorithms for various type of VRP.
Surveys of existing methods for multi-objective problems were presented in Jozefowiez et al. (2008) and Zhou et al. (2011). In Jozefowiez et al. (2008), the authors examined multiobjective versions of several variants of the VehicleRouting Problem (VRP) in terms of their objectives, their characteristics and the types of proposed algorithms to solve them. A survey of the state of the art of the multi-objective evolutionary algorithms was proposed by Zhou et al. (2011). This papers covers algorithms frameworks for multiobjective combinatorial problems during the last eight years. However, in the literature reviewed, there are few works considering the multi-objective version of the MDVRPB. Multiobjective metaheuristic approaches for combinatorial problems were presented in Doerner et al. (2004), Liu et al. (2006) and Lau et al. (2009). A multiobjective methodology by Pareto Ant Colony Optimization for solving a portfolio problem was introduced by Doerner et al. (2004). A multi-objective mixed zero-one integer-programming model for the vehiclerouting problem with balanced workload and delivery time was introduced by Liu et al. (2006). In this work, a heuristic-based solution method was developed. A fuzzy multi-objective evolutionary algorithm for the problem of optimization of vehiclerouting problems with multiple depots, multiple customers, and multiple products was proposed by Lau et al. (2009). In this work, two objectives were considered: minimization of the traveling distance and also the traveling time.
As far as we know, the coevolutionary paradigm has never been applied to the MDVRP. With regard to vehiclerouting in general, a large scale capacitated arc routing problem is addressed in Mei, Li, and Yao (2014) using a coevolutionary algorithm. In this work, the routes are grouped into different subsets to be optimized and prob- lem instances with more than 300 edges are solved. A multi-objective capacitated arc routing problem is also studied in Shang et al. (2014). A coevolutionary algorithm is presented in Wang and Chen (2013b) for a pickup and delivery problem with time windows. To minimize the number of vehicles and the total traveling distance, the authors use two populations: one for diversiﬁcation purposes and the other for intensiﬁcation purposes. In the scheduling domain, a competi- tive coevolutionary quantum genetic algorithm for minimizing the makespan of a job shop scheduling problem is reported in Gu, Gu, Cao, and Gu (2010).
O Single VehicleRouting Problem with Deliveries and Selective Pickups (SVR- PDSP) ´e uma varia¸c˜ao do cl´assico VehicleRouting Problem (VRP). Tem recebido pouca aten¸c˜ao, apesar de possuir muitas aplica¸c˜oes pr´aticas em cen´arios de log´ıstica reversa, como por exemplo em f´abricas de bebidas, que ao mesmo tempo em que h´a uma demanda de supermercados e outras lojas por garrafas cheias, tamb´em existe uma demanda pela coleta de garrafas vazias a retornar para o dep´osito a fim de serem limpas e reutilizadas. Al´em disso tamb´em existe o Multiple VehicleRouting Problem with De- liveries and Selective Pickups (MVRPDSP), o qual compartilha as mesmas aplica¸c˜oes, podendo at´e ser considerado mais pr´atico do que o SVRPDSP, j´a que em casos reais s˜ao usuais cen´arios com multiplos ve´ıculos. Entretanto, com rela¸c˜ao ao MVRPDSP n˜ao ´e de nosso conhecimento qualquer abordagem na literatura. Neste trabalho, para o SVR- PDSP, em termos de abordagens heur´ısticas, s˜ao propostos um Algoritmo Evolucion´ario H´ıbrido que faz uso de uma estrat´egia de data mining em seus operadores de crossover e muta¸c˜ao, al´em de um Variable Neighborhood Descent Algorithm (VND). Al´em disso, tamb´em ´e proposto um Branch&Cut para uma formula¸c˜ao matem´atica da literatura e uma nova formula¸c˜ao, a qual utiliza um tipo diferente de restri¸c˜oes para elimina¸c˜ao de subciclos. Com rela¸c˜ao ao MVRPDSP, s˜ao propostas duas formula¸c˜oes matem´aticas baseadas nos modelos matem´aticos do SVRPDSP, e uma heur´ıstica construtiva h´ıbrida do tipo cluster-first. Resultados experimentais indicam que a formula¸c˜ao proposta para o SVRPDSP possui um desempenho muito superior `as da literatura, conseguindo en- contrar a solu¸c˜ao ´otima para mais da metade das instˆancias. Para o MVRDPSP foram criadas instˆancias de teste e s˜ao reportados v´arios bons resultados, incluindo algumas solu¸c˜oes ´otimas.
Abstract: Problem statement: In this study, we considered the application of a genetic algorithm to vehiclerouting problem with time windows where a set of vehicles with limits on capacity and travel time are available to service a set of customers with demands and earliest and latest time for serving. The objective is to find routes for the vehicles to service all the customers at a minimal cost without violating the capacity and travel time constraints of the vehicles and the time window constraints set by the customers. Approach: We proposed a genetic algorithm using an optimized crossover operator designed by a complete undirected bipartite graph that finds an optimal set of delivery routes satisfying the requirements and giving minimal total cost. Various techniques have also been introduced into the proposed algorithm to further enhance the solutions quality. Results: We tested our algorithm with benchmark instances and compared it with some other heuristics in the literature. The results showed that the proposed algorithm is competitive in terms of the quality of the solutions found. Conclusion/Recommendations: This study presented a genetic algorithm for solving vehiclerouting problem with time windows using an optimized crossover operator. From the results, it can be concluded that the proposed algorithm is competitive when compared with other heuristics in the literature.
ABSTRACT: An equipment replacement decision takes into account economic engineering models based on discounted cash flow (DCF) such as the Annual Equivalent Cost (AEC). Despite a large number of researches on industrial assets replacement, there is a lack of studies applied to farm goods. This study aimed at assessing an alternative model for economic decision analysis on farm machinery replacement, with no restrictions on the number of replacements and assessed goods during a defined timeline. The results of the hybrid model based on the combination of the vehiclerouting problem and the equipment replacement problem (RVPSE) applied to three different farm tractors showed the model reliability, providing a wider range of decisions for management support. KEYWORDS: economic engineering, annual equivalent cost, integer linear programming.
A fim de considerar o engarrafamento no planeja- mento da distribuição física, dentre os diversos conceitos de roteamento de veículos já estudados, o que mais se adere a esta realidade é o Time Dependent VehicleRouting Problem (TDVRP). No TDVRP tem-se uma frota de veículos com capacidade limitada que deve coletar ou entregar cargas a clientes a partir de um depósito central. Os clientes devem ser designados aos veículos que realizam rotas, de forma que o tempo total gasto seja minimizado. O tempo de via- gem entre dois clientes ou entre um cliente e o depósito de- pende de suas distâncias e também do momento do dia que o transporte é feito; por exemplo, nos horários de pico o tempo para deslocamento é maior devido ao congestiona- mento. As janelas de tempo para servir os clientes, ou seja, o período que os clientes podem ser atendidos, devem ser consideradas assim como a máxima duração permitida para cada rota (horário de trabalho do motorista) (Malandraki e Daskin, 1992). O TDVRP é, então, uma extensão do Pro- blema de Roteamento de Veículos (VRP) que pode levar em
Abstract: The transport activities usually involves several actors and vehicles spread out on a network of streets. This complex system intricate the techniques to deal with dynamic events usually present in transport operations. In this context, as could be noted in the literature review, the use of multi-agent systems (MAS) seems suitable to support the autonomous decision-making. This work presents an agent based system to deal with a dynamic vehiclerouting problem, more precisely, in a pick-up problem, where some tasks assigned to vehicles at the beginning of the operation could be transferred to others vehicles. The task transfer happens when the vehicle agents perceive that the cycle time can exceed the daily limit of working hours, and is done through a negotiation protocol called Vickrey. The proposed system allows a collaborative decision- making among the agents, which makes possible adjustments during the course of the planned route.
Basically we use a Data Mining strategy, in which every new individual has its route analyzed to extract patterns (sequence of customers) within a given range [minP atternSize, maxP atternSize]. Each pattern found is stored in a structure called patternsList along with the frequency it has appeared in the solutions already ana- lyzed. In addition to these information, we also keep record of the average cost of the route in which the pattern was found so as to improve the robustness of the eval- uation criteria that decides how good a pattern is. Therefore we have two types of data to evaluate a pattern: frequence and average cost. Good patterns have high frequency and low average cost. Since cost value is usually much higher than the frequency value, this data must be normalized. Lets call nF requency the normal- ized frequency value, nAvgCost the normalized average cost. Therefore we define qualityIndex = (1 − nAvgCost) + nF requency, as the value used to evaluate the pat- terns, since it considers both measures. The closer to 2 the better. This is not the first time an approach combining a heuristic and a data mining algorithm is proposed for a vehiclerouting problem. In , Santos et al proposed 4 approaches for a single vehiclerouting problem, including one that combines a Genetic Algorithm with the data mining algorithm Apriori. Our approach is not based on their approach and is fairly different from the algorithm they developed.
13.1 The VehicleRouting Problem 177 The contribution of this work is then to define a powerful yet simple cMA capable of competing with the best known approaches for solving CVRP in terms of accuracy (final cost) and computational effort (the number of evalua- tions made). For that purpose, we test our algorithm over the mentioned large selection of instances (160), which will allow us to guarantee deep and mean- ingful conclusions. Besides, we compare our results against the best existing ones in the literature, some of which we even improve. In  the reader can find a seminal work with a comparison between our algorithm and some other known heuristics for a reduced set of 8 instances. In that work, we showed the advantages of embedding local search techniques into a cGA for solving CVRP, since our hybrid cGA was the best algorithm out of all those compared in terms of accuracy and time. Cellular GAs represent a paradigm much simpler to comprehend and customize than others such as tabu search (TS) [97, 249] and similar (very specialized or very abstract) algorithms [37, 207]. This is an important point too, since the greatest emphasis on simplicity and flexibility is nowadays a must in research to achieve widely useful contributions .
Abstract: A phenomenon-inspired meta-heuristic algorithm, harmony search, imitating music improvisation process, is introduced and applied to vehiclerouting problem, then compared with one of the popular evolutionary algorithms, genetic algorithm. The harmony search algorithm conceptualized a group of musicians together trying to search for better state of harmony. This algorithm was applied to a test traffic network composed of one bus depot, one school and ten bus stops with demand by commuting students. This school bus routing example is a multi-objective problem to minimize both the number of operating buses and the total travel time of all buses while satisfying bus capacity and time window constraints. Harmony search could find good solution within the reasonable amount of time and computation.
A vehiclerouting problem with time windows (VRPTW) is an important problem with many real applications in a transportation problem. The optimum set of routes with the minimum distance and vehicles used is determined to deliver goods from a central depot, using a vehicle with capacity constraint. In the real cases, there are other objective functions that should be considered. This paper considers not only the minimum distance and the number of vehicles used as the objective function, the customer’s satisfaction with the priority of customers is also considered. Additionally, it presents a new model for a bi-objective VRPTW solved by a revised multi-choice goal programming approach, in which the decision maker determines optimistic aspiration levels for each objective function. Two meta-heuristic methods, namely simulated annealing (SA) and genetic algorithm (GA), are proposed to solve large-sized problems. Moreover, the experimental design is used to tune the parameters of the proposed algorithms. The presented model is verified by a real-world case study and a number of test problems. The computational results verify the efficiency of the proposed SA and GA.
Abstract: Problem statement: The Capacitated VehicleRouting Problem (CVRP) is a well-known combinatorial optimization problem which is concerned with the distribution of goods between the depot and customers. It is of economic importance to businesses as approximately 10-20% of the final cost of the goods is contributed by the transportation process. Approach: This problem was tackled using an Ant Colony Optimization (ACO) combined with heuristic approaches that act as the route improvement strategies. The proposed ACO utilized a pheromone evaporation procedure of standard ant algorithm in order to introduce an evaporation rate that depends on the solutions found by the artificial ants. Results: Computational experiments were conducted on benchmark data set and the results obtained from the proposed algorithms shown that the application of combination of two different heuristics in the ACO had the capability to improve the ants’ solutions better than ACO embedded with only one heuristic. Conclusion: ACO with swap and 3-opt heuristic has the capability to tackle the CVRP with satisfactory solution quality and run time. It is a viable alternative for solving the CVRP.
Abstract: Many cities are facing difficulties in urban mobility and therefore are imposing restrictions on the movement of larger trucks. Thus, logistics companies developed a two level logistics strategy based on Urban Distribution Centers (CDU) that receives larger trucks and split the cargo to put in small trucks to distribute to customers. To support this type of logistics planning, this paper presents an adaptation of a mathematical model based on the Two-echelon capacitated VehicleRouting Problem (2E-CVRP) to plan the routes from the central depot to the satelites and from these to the clients. The model was applied to the logistics of Correios in the metropolitan area of the Espírito Santo, Brazil, and instances with up to 4 CDU and 25 clients were tested using CPLEX solver 12.6 obtaining routes for deliveries at both levels.
Abstract: The paper deals with the design of a route elimination (RE) algorithm for the vehiclerouting problem with time windows (VRPTW). The problem has two objectives, one of them is the minimal number of routes the other is the minimal cost. To cope with these objectives effectively two-phase solutions are often suggested in the relevant literature. In the first phase the main focus is the route elimination, in the second one it is the cost reduction. The algorithm described here is a part of a complete VRPWT study. The method was developed by studying the graph behaviour during the route elimination. For this purpose a model -called “Magic Bricks” was developed. The computation results on the Solomon problem set show that the developed algorithm is competitive with the best ones.