A Solution Proposal to Vehicle Routing Problem with Integer Linear Programming: A Distributor Company Sample

It was aimed to minimize the total distance of the routes under the capacity constraint of the routes that a distributor company has drawn in the direction of the demands. To this end, a route to Gebze-based steel production and distribution was drawn up to meet all the demands of a fabrication plant. In order to determine the minimum total distance routes, the solution recommendation by adapting the Capacity Constrained Vehicle Routing Problem (CVRP) which is one of the basic route problems using Branch and Cut algorithm of 0-1 Integer Linear Programming (ILP) was introduced. Distances between the nodes that make up the route are measured via Google Maps. Optimal solutions were obtained by using LINDO computer software to solve the problem.

An improved Ant Colony System for the Sequential Ordering Problem

It is not rare that the performance of one metaheuristic algorithm can be improved by incorporating ideas taken from another. In this article we present how Simulated Annealing (SA) can be used to improve the efficiency of the Ant Colony System (ACS) and Enhanced ACS when solving the Sequential Ordering Problem (SOP). Moreover, we show how the very same ideas can be applied to improve the convergence of a dedicated local search, i.e. the SOP-3-exchange algorithm. A statistical analysis of the proposed algorithms both in terms of finding suitable parameter values and the quality of the generated solutions is presented based on a series of computational experiments conducted on SOP instances from the well-known TSPLIB and SOPLIB2006 repositories. The proposed ACS-SA and EACS-SA algorithms often generate solutions of better quality than the ACS and EACS, respectively. Moreover, the EACS-SA algorithm combined with the proposed SOP-3-exchange-SA local search was able to find 10 new best solutions for the SOP instances from the SOPLIB2006 repository, thus improving the state-of-the-art results as known from the literature. Overall, the best known or improved solutions were found in 41 out of 48 cases.Comment: 30 pages, 8 tables, 11 figure

An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem

Capacitated Vehicle Routing Problem (CVRP) is considered as one of the most famous specialized forms of VRP that has attracted considerable attention from researchers. This problem belongs to complex combinatorial optimization problems included in the NP-Hard Problem category, which is a problem that needs difficult computation. This paper presents an improvement of Ant Colony System (ACS) to solve this problem. In this study, the problem deals with a few vehicles which are used for transporting products to specific places. Each vehicle starts from a main location at different times every day. The capacitated vehicle routing problem (CVRP) is defined to serve a group of delivery customers with known demands. The proposed study seeks to find the best solution of CVRP by using improvement ACS with the accompanying targets: (1) To decrease the distance as long distances negatively affect the course of the process since it consumes a great time to visit all customers. (2) To implement the improvement of ACS algorithm on new data from the database of CVRP. Through the implementation of the proposed algorithm better results were obtained from the results of other methods and the results were compared

Construção de rotas no transporte de produtos biológicos de uma unidade hospitalar

O transporte de produtos biológicos é só um pequeno exemplo de como vários problemas podem ser resolvidos com uma ferramenta de apoio à decisão, independentemente da área onde se inserem. Esta dissertação descreve um caso de estudo desenvolvido durante o estágio profissional numa empresa do ramo hospitalar, com o objetivo da criação de rotas com recolhas e janelas temporais para o transporte de produtos biológicos colhidos fora do laboratório onde são processados. Para a obtenção da rota, foi desenvolvida uma ferramenta de apoio à decisão baseada num modelo matemático de programação inteira que resolve problemas de roteamento de veículos com recolhas e janelas temporais - VRPPTW. A ferramenta de apoio à decisão permitiu analisar três cenários possíveis em que a diferença entre eles passa pela decisão de instalar centrífugas nos diversos pontos de colheitas. Ambas as soluções encontradas satisfazem as restrições impostas, face ao modelo atual da empresa, que não estava a cumprir com os tempos limite de entrega. A construção do modelo matemático permitiu construir a rota de modo eficiente, tendo em conta as distâncias percorridas, tempos de serviço, tempos de deslocação e tempo total da rota. Com a análise e consequente escolha da melhor solução obteve-se uma poupança de aproximadamente 54% nos custos da Rota, com uma diminuição no tempo total da rota de 60% relativamente ao estado inicial da rota, mesmo com a adição de mais um ponto de recolha, traduzindo numa libertação de 02:30h do motorista para outros serviços. Estes resultados são válidos para um investimento em duas centrífugas, que com os ganhos obtidos, recupera-se em dois anos e nove meses.Transporting biological products is just a small example of how various problems can be solved with a decision support tool, regardless where they are located. This dissertation describes a case study developed during the professional internship in a hospital company, with the objective of creating routes with pick-ups and time windows to transport biological products harvested outside the laboratory where they are processed. In order to obtain the route, a decision support tool based on an integer mathematical programming model was developed to solve the vehicle routing problems with pick-ups and time windows - VRPPTW. The decision support tool allowed to analyze three possible scenarios in which the difference between them involves the decision to install centrifuges at the various harvesting points. Both solutions fulfill the restrictions imposed, given the current model of the company, which didn’t obey the delivery times. The construction of the mathematical model made it possible to construct the route efficiently, considering the distances traveled, service times, travel times and total route time. The analysis and consequent choice of the best solution resulted in a saving of approximately 54% in Route costs, with a reduction in the total route time of 60% compared to the initial state of the route, even with the addition of one more pick-up point, translated at 02: 30h driver's release for other services. These results are valid for an investment in two centrifuges, which with the gains obtained, recover in two years and nine months