Browsing by Author "Borenstein, Denis"

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Column generation based heuristic framework for the multiple-depot vehicle type scheduling problem
(ELSEVIER LTD, 2015-12-01) Borenstein, Denis
The multiple-depot vehicle-type scheduling problem (MDVTSP) is an extension of the classic multiple-depot vehicle scheduling problem (MDVSP), where heterogeneous fleet is considered. Although several mathematical formulations and solution methods have been developed for the MDVSP, the MDVTSP is still relatively unexplored. Large instances of the MDVTSP (involving thousands of trips and several depots and vehicle types) are still difficult to solve in a reasonable time. We introduce a heuristic framework, combining time-space network, truncated column generation (TCG) and state space reduction, to solve large instances of the MDVTSP. Extensive testing was carried out using random generated instances, in which a peak demand distribution was defined based on real-world data from public transportation systems in Brazil. Furthermore, experiments were carried out with a real instance from a Brazilian city. The framework has been implemented in several algorithm variants, combining different developed preprocessing procedures, such as state space reduction and initial solutions for the TCG. Computational results show that all developed algorithms obtained very good performances both in quality and efficiency. The best solutions, considering simultaneously quality and efficiency, were obtained in the heuristics involving state space reduction.
Development of an integrated decision-making method for an oil refinery restructuring in Brazil
(ELSEVIER LTD, 2016-09-15) Borenstein, Denis
This paper describes an integrated decision analysis method to support the managing board to define a restructuring plan for a small oil refinery in south Brazil. The refinery is facing an extreme crisis situation due to the obsolescence of its production plant. The decision approach proposed in this paper consists of four phases. Initially, potentially performing restructuring alternatives were identified, as well a set of criteria covering the dimensions of corporate sustainability. Based on the relative importance evaluation of each criteria given by a group of decision-makers, and on the performance of the alternatives in each of the criteria, a fuzzy decision-making method, called FETOPIS, was applied for ranking the alternatives. The information resulting from this analysis, along with economic data, was used in a portfolio optimization model to identify restructuring investment projects (RIPs), a combination of feasible restructuring alternatives. FETOPSIS was used again to generate overall performance scores of each RIP, aggregating the individual performances of the constituent alternatives. The application of the method in the refinery demonstrated the efficiency and efficacy of the proposed approach to facilitate the understanding and exploitation of the problem, considering simultaneously several distinct and conflicting dimensions.
Hybrid fuzzy MADM ranking procedure for better alternative discrimination
(ELSEVIER LTD, 2016-04-01) Borenstein, Denis
In this paper, we propose a hybrid fuzzy decision making approach, combining elements of fuzzy-ELECTRE and Fuzzy-TOPSIS, towards a new ranking procedure. The main objective of FETOPSIS is to offer rankings with good alternative discriminatory power to decision makers (DMs). This research work was motivated by a real case study in which multiple attribute decision making techniques were used to select the best set of investment projects for the industrial restructuring of a small oil company in Brazil. After the application of Fuzzy-TOPSIS and ELECTRE II, the obtained rankings were quite deceptive from the DMs' point of view, either to very close scores or by the excess of indifferences among alternatives. Our developed approach uses the closeness coefficients to rank the alternatives, following Fuzzy-TOPSIS, however they are computed over the normalized fuzzy concordance and discordance indexes based on the ELECTRE family. Extensive computational experiments were performed to evaluate our method. The good results obtained by FETOPSIS in the experiments, both in terms of alternative discriminatory power of rankings, and eliminating ranking reversal cases, gave us the confidence to apply the method in the real case. The DMs praised the developed approach, since the obtained rankings were more discriminatory in the alternatives than both Fuzzy-TOPSIS and ELECTRE II, making it possible to select with confidence a set of suited alternatives.
Simple and efficient heuristic approach for the multiple-depot vehicle scheduling problem
(SPRINGER VERLAG, 2016-10-01) Borenstein, Denis
In this paper, a fast heuristic approach is proposed for solving the multiple depot vehicle scheduling problem (MDVSP), a well-known NP-hard problem. The heuristic is based on a two stage procedure. The first one applies two state space reduction procedures towards reducing the problem complexity. One procedure is based on the solutions of the single-depot vehicle scheduling for each depot, while the other uses the solution of a relaxed formulation of the MDVSP, in which a vehicle can finish its task sequence in a different depot from where it started. Next, the reduced problem is solved by employing a truncated column generation approach. The heuristic approach has been implemented in several variants, through different combinations of the reduction procedures, and tested on a series of benchmark problems provided by Pepin et al. (J Sched 12:17–30, 2009). The heuristic variants found solutions with very narrow gaps (below 0.7 %, on average) to best-known solutions (Pepin et al., J Sched 12:17–30, 2009), decreasing the required CPU time by an overall average factor of 17 in comparison with reported results in the literature (Otsuki and Aihara, J Heuristics 1–19, 2014).
Student selection in a Brazilian university: using a multi-criteria method
(2018) De Farias Aires, Renan Felinto; Ferreira, Luciano; De Araújo, Afranio Galdino; Borenstein, Denis
Student selection is a complex decision-making process, in which several criteria need to be considered simultaneously. In this paper, we address this problem for a Brazilian university that has created an interdisciplinary degree in which several intermediate selection processes are required during the course, defining the final title degree. The university is currently using an aggregated score based on the performance of a student in the course. However, this method is facing difficulties in selecting the best students, because deficiencies in the way transferred, dropped and quit course credits are accounted for. As a possible alternative for the current method, we developed a hybrid ranking algorithm, called ELECTRE–TOPSIS (E–T). This method combines elements of the ELECTRE family and TOPSIS, two well-known multi-attribute analysis tools, to rank students based on objective criteria. Computational experiments and a case study were conducted to evaluate E–T. The results show that our approach provides quite competitive rankings in comparison with similar methods, through simultaneously eliminating ranking reversal and better balancing the formation time and the academic performance of the evaluated students.
Supply chain network optimization using a Tabu Search based heuristic
(BRAZILIAN INSTITUTE FOR INFORMATION IN SCIENCE AND TECHNOLOGY, 2016-01-01) Borenstein, Denis
This paper discusses the implementation and evaluation of a heuristic based on Tabu Search to optimize a supply chain network. To this end, a single-source model proposed by Farias & Borenstein (2012) was implemented. The problem was solved by adapting the Lee & Kwon method (2010), exchanging distribution centers (DCs) and arcs to find the lowest cost for a supply chain network. Twenty-two instances proposed by Farias & Borenstein (2012) were solved and the results indicate that, for the scenarios, the method applied presented good computational performance, obtaining results with 81.03% reduction of the average processing time. However, there was an increase of 4.98% in the average cost of the solutions obtained through the heuristic method when compared with the optimal results. Finally, the problem was solved for four other instances with real features, proving the efficiency of this heuristic for large-scale problems, considering that all solutions were obtained in less than 2 minutes of processing.
Supply chain network optimization using a Tabu Search based heuristic [Otimização da rede de uma cadeia de suprimentos com a utilização de uma heurística baseada em Busca Tabu]
(TAYLOR AND FRANCIS LTD., 2016-01-01) Borenstein, Denis
This paper discusses the implementation and evaluation of a heuristic based on Tabu Search to optimize a supply chain network. To this end, a single-source model proposed by Farias & Borenstein (2012) was implemented. The problem was solved by adapting the Lee & Kwon method (2010), exchanging distribution centers (DCs) and arcs to find the lowest cost for a supply chain network. Twenty-two instances proposed by Farias & Borenstein (2012) were solved and the results indicate that, for the scenarios, the method applied presented good computational performance, obtaining results with 81.03% reduction of the average processing time. However, there was an increase of 4.98% in the average cost of the solutions obtained through the heuristic method when compared with the optimal results. Finally, the problem was solved for four other instances with real features, proving the efficiency of this heuristic for large-scale problems, considering that all solutions were obtained in less than 2 minutes of processing.
The Brazilian scientific output published in journals: A study based on a large CV database
(ELSEVIER LTD, 2017-02-01) Borenstein, Denis
We assemble a massive sample of 180,000 CVs of Brazilian academic researchers of all disciplines from the Lattes platform. From the CVs we gather information on key variables related to the researchers and their publications. We find males are more productive in terms of quantity of publications, but the effect of gender in terms of research impact is mixed for individual groups of subject areas. For all fields of science, holding a PhD from abroad increases the chance for a researcher to publish in journals of higher impact. We also find that the more years a researcher takes to finish his or her doctorate, the more likely he or she will publish less thereafter, although in outlets of higher impact. The data also support the existence of an inverted U-shaped function relating research age and productivity.
Towards integrating retiming in vehicle type scheduling problem
(2018) Borenstein, Denis; Campoverde Campoverde, Jorge Arturo; Naula Sigua, Freddy Benjamín
In this paper, we propose an integer linear programming (ILP) aiming at optimizing timetabling generation and the Vehicle Type Scheduling Problem (VTSP), based on a time-space network (TSN). The model was defined as Vehicle Type Scheduling Problem with Sequential Changes of timetable (VTSP- SCT). Additionally, we developed a new methodology to insert time window to the proposed problem based on small changes on the TSN structure, with easy computational implementation and optimal solution at low computation run-times. By including small changes to the timetable and/or including time windows for timetabling trips, we introduced flexibility levels in the departure times of trips, resulting in operational advantages for the service provider. Since we use a very short time window interval, the current timetable is only slightly modified, minimally changing the passenger routines. The developed approaches were tested using random instances based on a Brazilian city. The VTSP-SCT with and without time windows have resulted in relevant savings in the daily operations of the public transportation service,reducing the required number of scheduled vehicles to carry out the historic demand.