Category Archives: Research

A BRILS metaheuristic for a non-smooth flow-shop problems with failure-risk costs

This paper analyzes a realistic variant of the permutation flow-shop problem (PFSP) by considering a non-smooth objective function that takes into account not only the traditional makespan cost but also failure-risk costs due to uninterrupted operation of machines. After completing a literature review on the issue, the paper formulates an original mathemati- cal model to describe this new PFSP variant. Then, a Biased-Randomized Iterated Local Search (BRILS) algorithm is proposed as an efficient solving approach. An oriented (biased) random behavior is introduced in the well-known NEH heuristic to generate an initial solution. From this initial solution, the algorithm is able to generate a large number of alternative good solutions without requiring a complex setting of parameters. The relative simplicity of our approach is particularly useful in the presence of non-smooth objective functions, for which exact optimization methods may fail to reach their full potential. The gains of considering failure-risk costs during the exploration of the solution space are an- alyzed throughout a series of computational experiments. To promote reproducibility, these experiments are based on a set of traditional benchmark instances. Moreover, the performance of the proposed algorithm is compared against other state-of-the-art metaheuristic approaches, which have been conveniently adapted to consider failure-risk costs during the solving process. The proposed BRILS approach can be easily extended to other combinatorial optimization problems with similar non-smooth objective functions.

Solving a Large-scale Real Heterogeneous Fleet VRP with Multi-trips and Docking Constraints

Distribution planning is crucial for most companies since goods are rarely produced and consumed at the same place. Distribution costs, in addition, can be an important component of the final cost of the products. In this paper, we study a VRP variant inspired on a real case of a large distribution company. In particular, we consider a VRP with a heterogeneous fleet of vehicles that are allowed to perform multiple trips. The problem also includes docking constraints in which some vehicles are unable to serve some particular customers, and a realistic objective function with vehicles’ fixed and distance-based costs and a cost per customer visited. We design a trajectory search heuristic called GILS-VND that combines Iterated Local Search (ILS), Greedy Randomized Adaptive Search Procedure (GRASP) and Variable Neighborhood Descent (VND) procedures. This method obtains competitive solutions and improves the company solutions leading to significant savings in transportation costs.

Coelho V.N., Grasas A., Ramalhinho H., Coelho I.M., Souza M.J.F. (2015), An ILS-based Algorithm to Solve a Large-scale Real Heterogeneous Fleet VRP with Multi-trips and Docking Constraints, European Journal of Operational Research (accepted for publication September 2015) doi:10.1016/j.ejor.2015.09.047.

On the UPF web (in Catalan)

MIC 2015, Agadir, Marocco

Helena has presented also the work “Simheuristics for Supply Chain Management” at the MetaheuriIMG_2057stics International Conference (MIC 2015) at Agadir, Marocco.

MIC is the well know conference in Metaheuristics. Helena has been part of the Program Committee for many editions, and she, together with Angel Juan (UOC), will organise the MIC 2017 in Barcelona, Spain. She also had the opportunity to talk with the leaders researchers in the area of Metaheuristics, as Mauricio Resende (Amazon), Celso Ribeiro (UFF), Éric Taillard (UASW), Angél Juan (UOC), Martin G. Ravetti (UFMG), Fred Glover (UC), etc.

You can download the presentation at the Conferences page of this blog.

IO2015 – XVII Congresso da APDIO “IO & BIG DATA “

Helena Ramalhinho had presented the article “Simheuristics for Supply Chain Management” at the IO2015 – XVII Congresso da APDIO “IO & BIG DATA ” in Portalegre, Portugal. This is he internationalIMG_2608 conference organized by APDIO, the Portuguese Association of Operations Research.

Supply Chain Management (SCM) is a relevant topic in today’s business and academia. It is related with the management of all activities along a supply chain. SCM is not just a sum of activities along the supply chain, but aspects as integration and coordination should be taken into account to a better performance. Continue reading


The Business Analytics Research Group participates in the SMARTLOGISTICS@IB project funded by CYTED – PROGRAMA IBEROAMERICANO DE CIENCIA Y TECNOLOGIA PARA EL DESARROLLO (Ibero-American Science and Technology for Development Programme)

See the Business Analytics Research Group Blog: Smartlogistics@IB

GreenCOOP: Hybrid Methods for Horizontal Cooperation in Green Transportation and Logistics

Enterprises in the retailing, logistics and transportation sectors have to face several difficult challenges related to the complexity of logistics and distribution strategies. Among others, they have to design business and distribution strategies as well as policies which combine competitiveness, and economic efficiency with sustainability criteria. These issues are critical, especially for small and medium enterprises (SME), since they hardly have the economic and human resources necessary to implement and manage the complex mathematical methods associated with logistics optimization. One strategy that SMEs can follow to become more competitive is to collaborate with other companies (Horizontal Cooperation), allowing the use of economies of scale.

Fortunately, new quantitative methods can be developed now thanks to theoretical advances as well as to the increase in computer power. This is the case of hybrid methods combining metaheuristics, simulation, exact methods, parallel and distributed computing, multi-agent approaches, etc. In particular, as a new research field, ‘simheuristics’ evolves from the simulation-optimization knowledge field and goes one step further by proposing the integration of simulation techniques, metaheuristics, and Internet computing as the most efficient way to deal with the uncertainty and complexity levels which characterize most real-life problems in logistics and transportation.

The Business Analytics Group is the UPF member of this project. Helena Ramalhinho is leading the subproject on BusinessCOOP: Business Analytics Models for Horizontal Cooperation in Transportation and Logistics.

The other two subprojects are led by Javier Faulin, Universidad Publica de Navarra (SustanaibleCOOP: Horizontal Cooperation and Environmental Costs in the Sustainable Management of Goods Transportation) and Angel Juan, Universitat Open of Catalonia (ComputerCOOP: Computer-based decision support for Horizontal Cooperation in Transportation and Logistics).

The project was funded by the Spanish Ministry of Economy and Competitiveness, Spain.