Advanced Optimization Models in Waste Management

Diplomová práce se zabývá optimalizací svozu odpadu pro středně velká města. Model úlohy zohledňuje požadavky vzešlé z praxe. K jejímu řešení byl navržen původní memetický algoritmus, který byl implementován v jazyce C++.This thesis deals with an optimization of waste collection in a mid-sized town. The model is formulated based on requirements from a real process. To deal with this problem, the original memetic algorithm was developed and implemented in C++.

The Multi Trip Vehicle Routing Problem with Time Windows and Release Dates

The Multi-Trip Vehicle Routing Problem with Time Windows and Release Dates is a variant of the Multi-Trip Vehicle Routing Problem where a time windows is associated with each customer and a release date is associated with each merchandise to be delivered at a certain client. The release date represents the moment the merchandise becomes available at the depot for final delivery. The problem is relevant in city logistics context, where delivery systems based on city distribution centers (CDC) are studied. Trucks arrive at the CDC during the whole working day to deliver goods that are transferred to eco-friendly vehicles in charge of accomplish final deliveries to customers. We propose a population-based algorithm for the problem based on giant tour representation of the chromosomes as well as a split procedure to obtain solutions from individuals

Vehicle Routing and Scheduling Problem for a multi-period, multi-perishable product system with time window: A Case study

[EN] The well-known Vehicle Routing Problem (VRP) is to find proper sequence of routes in order to minimize transportation costs. In this paper, a mixed-integer programming model is presented for a food distributer company and the model outputs are to determine the optimal routes and amount of pickup and delivery. In the objective function, the costs of transportation, holding, tardiness and earliness are considered simultaneously. The proposed model with respect to real conditions is multi-period and has two different time periods: one for dispatching vehicles to customers and suppliers and the other for receiving customers’ orders. Time window and split pickup and delivery are considered for perishable products. The proposed model is nonlinear and will be linearized using exact techniques. At the end, model is solved using GAMS and the sensitivity analysis is performed. The results indicate that the trend of changes in holding and transportation costs in compared to tardiness and earliness costs are closed together and are not so sensitive to demand changes.Rashidi Komijan, A.; Delavari, D. (2017). Vehicle Routing and Scheduling Problem for a multi-period, multi-perishable product system with time window: A Case study. International Journal of Production Management and Engineering. 5(2):45-53. doi:10.4995/ijpme.2017.5960SWORD455352DENG, A., MAO, C., & ZHOU, Y. (2009). Optimizing Research of an Improved Simulated Annealing Algorithm to Soft Time Windows Vehicle Routing Problem with Pick-up and Delivery. Systems Engineering - Theory & Practice, 29(5), 186-192. doi:10.1016/s1874-8651(10)60049-xAndersson, H., Hoff, A., Christiansen, M., Hasle, G., & Løkketangen, A. (2010). Industrial aspects and literature survey: Combined inventory management and routing. Computers & Operations Research, 37(9), 1515-1536. doi:10.1016/j.cor.2009.11.009Baldacci, R., Mingozzi, A., & Roberti, R. (2012). Recent exact algorithms for solving the vehicle routing problem under capacity and time window constraints. European Journal of Operational Research, 218(1), 1-6. doi:10.1016/j.ejor.2011.07.037Belfiore, P., & Yoshizaki, H. T. Y. (2013). Heuristic methods for the fleet size and mix vehicle routing problem with time windows and split deliveries. Computers & Industrial Engineering, 64(2), 589-601. doi:10.1016/j.cie.2012.11.007Cacchiani, V., Hemmelmayr, V.C., Tricoire, F., (2012). A set-covering based heuristic algorithm for the periodic vehicle routing problem. Discrete Applied Mathematics, 163(1), 53-64. https://doi.org/10.1016/j.dam.2012.08.032Cattaruzza, D., Absi, N., Feillet, D., & Vidal, T. (2014). A memetic algorithm for the Multi Trip Vehicle Routing Problem. European Journal of Operational Research, 236(3), 833-848. doi:10.1016/j.ejor.2013.06.012Çetinkaya, C., Karaoglan, I., & Gökçen, H. (2013). Two-stage vehicle routing problem with arc time windows: A mixed integer programming formulation and a heuristic approach. European Journal of Operational Research, 230(3), 539-550. doi:10.1016/j.ejor.2013.05.001Eksioglu, B., Vural, A. V., & Reisman, A. (2009). The vehicle routing problem: A taxonomic review. Computers & Industrial Engineering, 57(4), 1472-1483. doi:10.1016/j.cie.2009.05.009Hasani-Goodarzi, A., & Tavakkoli-Moghaddam, R. (2012). Capacitated Vehicle Routing Problem for Multi-Product Cross- Docking with Split Deliveries and Pickups. Procedia - Social and Behavioral Sciences, 62, 1360-1365. doi:10.1016/j.sbspro.2012.09.232Rahimi-Vahed, A., Gabriel Crainic, T., Gendreau, M., & Rei, W. (2015). Fleet-sizing for multi-depot and periodic vehicle routing problems using a modular heuristic algorithm. Computers & Operations Research, 53, 9-23. doi:10.1016/j.cor.2014.07.004Shahin Moghadam, S., Fatemi Ghomi, S. M. T., & Karimi, B. (2014). Vehicle routing scheduling problem with cross docking and split deliveries. Computers & Chemical Engineering, 69, 98-107. doi:10.1016/j.compchemeng.2014.06.015Silva, M. M., Subramanian, A., & Ochi, L. S. (2015). An iterated local search heuristic for the split delivery vehicle routing problem. Computers & Operations Research, 53, 234-249. doi:10.1016/j.cor.2014.08.005Taş, D., Jabali, O., & Van Woensel, T. (2014). A Vehicle Routing Problem with Flexible Time Windows. Computers & Operations Research, 52, 39-54. doi:10.1016/j.cor.2014.07.005Yu, B., & Yang, Z. Z. (2011). An ant colony optimization model: The period vehicle routing problem with time windows. Transportation Research Part E: Logistics and Transportation Review, 47(2), 166-181. doi:10.1016/j.tre.2010.09.010Zhang, S., Lee, C. K. M., Choy, K. L., Ho, W., & Ip, W. H. (2014). Design and development of a hybrid artificial bee colony algorithm for the environmental vehicle routing problem. Transportation Research Part D: Transport and Environment, 31, 85-99. doi:10.1016/j.trd.2014.05.01

Hybrid metaheuristics for solving multi-depot pickup and delivery problems

In today's logistics businesses, increasing petrol prices, fierce competition, dynamic business environments and volume volatility put pressure on logistics service providers (LSPs) or third party logistics providers (3PLs) to be efficient, differentiated, adaptive, and horizontally collaborative in order to survive and remain competitive. In this climate, efficient computerised-decision support tools play an essential role. Especially, for freight transportation, e efficiently solving a Pickup and Delivery Problem (PDP) and its variants by an optimisation engine is the core capability required in making operational planning and decisions. For PDPs, it is required to determine minimum-cost routes to serve a number of requests, each associated with paired pickup and delivery points. A robust solution method for solving PDPs is crucial to the success of implementing decision support tools, which are integrated with Geographic Information System (GIS) and Fleet Telematics so that the flexibility, agility, visibility and transparency are fulfilled. If these tools are effectively implemented, competitive advantage can be gained in the area of cost leadership and service differentiation. In this research, variants of PDPs, which multiple depots or providers are considered, are investigated. These are so called Multi-depot Pickup and Delivery Problems (MDPDPs). To increase geographical coverage, continue growth and encourage horizontal collaboration, efficiently solving the MDPDPs is vital to operational planning and its total costs. This research deals with designing optimisation algorithms for solving a variety of real-world applications. Mixed Integer Linear Programming (MILP) formulations of the MDPDPs are presented. Due to being NP-hard, the computational time for solving by exact methods becomes prohibitive. Several metaheuristics and hybrid metaheuristics are investigated in this thesis. The extensive computational experiments are carried out to demonstrate their speed, preciseness and robustness.Open Acces

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

A Metaheuristic Method for the Multi Trip Vehicle Routing Problem

National audienceIn recent years the number of passengers and freight vehicles increased in urban areas causing traffic congestion and increasing air and noise pollution. The need of an efficient distribution system that takes into account distribution cost, but at the same time considers environmental aspects aims the concept of city logistics. Vehicles could have limited capacity, due to laws restriction imposed and the narrowness of streets that characterize historical parts of downtowns. Then, it seems normal to allow vehicles accomplish several trips during the working day. MTVRP arises in this context. A MA is proposed to face the problem

A constructive heuristic for the multi-compartment vehicle routing problem: an approach for a fuel distribution company

In this paper, we suggest a Decision Support System (DSS) for route planning. This DSS was developed in a real context in a fuel distribution company. This company distributes three types of fuel through multi-compartment vehicles with limited capacity, and satisfying delivery time windows imposed by the customers. Two approaches for this problem were considered: The first one considers the route planning without replenishments while the second one considers the multi-trip case. The solution method is based on a Clarke and Wright savings algorithm incorporating all the constraints referred to above. Both approaches were tested using real instances. The savings for the company, in terms of the distribution process, were identified in the computational results. The DSS may provide an effective support to a complex decision problem.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools