The Position-Aware-Market: Optimizing Freight Delivery for Less-Than-Truckload Transportation

The increasing competition faced by logistics carriers requires them to ship at lower cost and higher efficiency. In reality, however, many trucks are running empty or with a partial load. Bridging such residual capacity with real time transportation demand enhances the efficiency of the carriers. We therefore introduce the Position-Aware-Market (PAM), where transportation requests are traded in real time to utilize transportation capacities optimally. In this paper we mainly focus on the decision support system for the truck driver, which solves a profit- maximizing Pickup and Delivery Problem with Time Windows (PM-PDPTW). We propose a novel Recursive Branch-and-Bound algorithm that solves the problem optimally, and apply it to a Tabu-Search heuristic for larger problem instances. Simulations show that problems with up to 50 requests can be solved optimally within seconds. Larger problems with 200 requests can be solved approximately by Tabu-Search in seconds, retaining 60% of the optimal profit

Supporting product distribution decisions of smallholder farmers

Smallholder farmers are usually very constrained in terms of market access, due to, among other factors, the low production volumes and subsequent lack of economies of scale, variable quality, difficulty in planning and unavailability of distribution channels. In some countries, alternative markets have emerged, in order to facilitate smallholder farmers’ access to markets. These can take the form of government feeding programs, that aim at providing an outlet for the smallholder farmer products, giving them priority in supplying public sector organisations. Such a program is the PNAE in Brazil, where local smallholder farmers can supply schools with raw materials for meals. This work aims to support smallholder farmers in distribution related decision-making. More specifically, it aims to allow farmers to maximise the profit from their participation in the government feeding programs through guiding them in the complex supply decision-making and product distribution planning processes. The paper presents the related method developed, as well as the results from a preliminary application of the method in a case study of a rural settlement in Brazil

Exact Algorithm for the Capacitated Team Orienteering Problem with Time Windows

The capacitated team orienteering problem with time windows (CTOPTW) is a problem to determine players' paths that have the maximum rewards while satisfying the constraints. In this paper, we present the exact solution approach for the CTOPTW which has not been done in previous literature. We show that the branch-and-price (B&P) scheme which was originally developed for the team orienteering problem can be applied to the CTOPTW. To solve pricing problems, we used implicit enumeration acceleration techniques, heuristic algorithms, and ng-route relaxations

Modelo Matemático e Meta-Heurística Simulated Annealing para Elaboração de Roteiros Turísticos com base no Tourist Trip Design Problem

Muito embora existam diversos pacotes de viagens com destinos predefinidos contemplando locais mais populares, nos últimos anos tem crescido a procura por soluções que criem roteiros personalizados voltados às necessidades de cada turista. Para suprir essa nova demanda surge o Problema de Elaboração de Rotas Turísticas (PERT) ou TouristTrip Design Problem (TTDP) o qual Van Oudheusden e Vansteenwegen (2007) sugerem o uso do OrienteeringProblem (OP) e suas extensões para resolução desta classe de problemas. Esta dissertação tem por objetivo o desenvolvimento de um modelo matemático e de uma meta-heurística SimulatedAnnealing (SA) para resolução do TouristTrip Design Problem (TTDP)

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

Rotas de recolha de produtos num armazém e rotas de distribuição de produtos numa zona de clientes

Relatório de estágio de mestrado, Universidade de Lisboa, Faculdade de Ciências, 2021O presente relatório diz respeito ao estágio realizado na Norparts, uma das empresas da Create Business que atua no mercado de distribuição de peças de automóveis, tendo as oficinas independentes como clientes alvo. Atualmente a Norparts tem armazéns em Frielas, Porto, Braga e Madrid. As peças são adquiridas a vários fornecedores, são armazenadas nos armazéns, seguem por sua vez para os mecânicos e lojas de venda e por fim chegam aos consumidores finais. Quando chegam aos armazéns, as peças têm que ser arrumadas nas prateleiras correspondentes para o efeito e quando chegam as ordens de encomenda, têm que ser recolhidas no armazém e posteriormente distribuídas pelos clientes. Com base no mapeamento que já estava feito para um dos armazéns, fez-se o mapeamento dos outros armazéns. Neste estágio apresentam-se e implementam-se heurísticas para o problema de determinação de rotas dentro de um armazém (order picking problem) e para o problema de determinação de rotas para uma zona de clientes, em que o objetivo é maximizar uma função profit garantindo que não se excede um tempo máximo da rota (orienteering problem). Considera-se neste problema a existência de janelas temporais Para a obtenção das rotas de picking dentro do armazém utiliza-se a heurística de inserção de menor custo com vista a obter uma primeira solução admissível e posteriormente as heurísticas 2-optimas e 1-optimal para o melhoramento da solução obtida anteriormente. Os resultados obtidos usando estas heurísticas foram comparados com os resultados obtidos antes da utilização das heurísticas nos armazéns em que já existiam rotas dentro do armazém. No caso do problema de determinação de rotas numa zona de clientes utiliza-se também uma heurística construtiva baseada no princípio de inserção de menor custo. Descreve-se também a obtenção dos dados para a zona de clientes em estudo e os resultados obtidos pela heurística.This report concerns the internship carried out at Norparts, one of the companies from Create Business that operates in the car parts distribution market with independent workshops as target customers. Norparts currently has warehouses in Frielas, Porto, Braga and Madrid. The parts are purchased from various suppliers, they are stored in warehouses, are distributed to mechanics and stores, and finally reach final consumers. When they arrive at the warehouses, the pieces have to be stored on the corresponding shelves and when the order list arrives, they must be collected at the warehouse and later distributed to customers. Based on the mapping that was already done for one of the warehouses, the other warehouses were mapped. At this internship, heuristics are presented and implemented for the problem of determining routes inside a warehouse (order picking problem) and for the problem of determining routes for a customers’ zone, where the objective is to maximize a profit function ensuring that a maximum route time is not exceeded (orienteering problem). In this problem, the existence of time windows is considered. To obtain the picking routes inside the warehouse, the cheapest insertion heuristic is used to obtain a first feasible solution and then the 2-optimal and 1-optimal heuristics to improve the solution obtained previously. The results obtained using these heuristics were compared with the results obtained before using the heuristics in the warehouses where there already existed routes defined. In the case of the problem of determining routes in a customers’ area, a constructive heuristic based on the principle of the cheapest insertion is also used. It is also described how to obtain the data for the customers’ area under study and the results obtained by the heuristic

Profitable Vehicle Routing Problem with Multiple Trips: Modeling and Variable Neighborhood Descent Algorithm

Abstract In this paper, we tackle a new variant of the Veh icle Routing Problem (VRP) which comb ines two known variants namely the Profitable VRP and the VRP with Mult iple Trips. The resulting problem may be called the Profitable Vehicle Routing Problem with Multiple Trips. The main purpose is to cover and solve a more co mplex realistic situation of the distribution transportation. The profitability concept arises when only a subset of customers can be served due to the lack of means or for insufficiency of the offer. In this case, each customer is associated to an economical profit wh ich will be integrated to the objective function. The latter contains at hand the total collected profit minus the transportation costs. Each vehicle is allowed to perform several routes under a strict workday duration limit. This problem has a very practical interest especially for daily distribution schedules with limited vehicle fleets and short course transportation networks. We point out a new discursive approach for p rofits quantificat ion wh ich is mo re significant than those existing in the literature. We propose four equivalent mathematical formu lations for the problem which are tested and compared using CPLEX solver on small-size instances. Optimal solutions are identified. For large-size instance, two constructive heuristics are proposed and enhanced using Hill Climbing and Variable Neighborhood Descent algorithm based on a specific three-arrays-based coding structure. Finally, extensive co mputational experiments are performed including randomly generated instances and an extended and adapted benchmark fro m literature showing very satisfactory results