Pascual Fernández

Estimating actual distances by norm functions: a comparison between the l k,p,θ -norm and the l b 1 , b 2 , θ -norm and a study about the selection of the data set

The aim of this paper is two-fold. First, the weighted lp-norm, which has proved to be an accurate distance predicting function and has been proposed by several authors as the most suitable predictor of distances, is compared through an empirical study with the l2b-norm, a function with the same number of parameters as the first one. The results show that neither distance function dominates the other. On the contrary, depending on the region considered either norm may be significantly better than the other. The second aim is to investigate how the selection of the data set representing the network of the region affects the ability of the distance predicting function for predicting distances, and to try to deduce how to obtain a suitable data set which adequately represents a given geographical region. Through another empirical study it is shown that the selection of the data set dramatically affects the accuracy of the predictions. To obtain a suitable data set it is important to choose a good sample size, and more importantly, the cities should be chosen so that they are distributed all over the region and represent the density of the cities in the region.

On the sum-max bicriterion path problem

Abstract In network analysis, there are many applications in which several weights associated with traversing each arc are given, so it is natural to consider multiple-objective path problems. Usually, there is no path which is simultaneously optimal with respect to all objective functions, so it will be necessary to obtain efficient paths of interest, i.e. paths for which there exists no other path that yields an improvement in one of the objective functions without causing a degradation in the others. Methods for determining efficient paths form part of a very extensive literature on multiple-objective optimization, most of them being proposed for objectives defined by sum functions. Our aim is to study the particular case of a bicriterion problem whose objective functions are defined by a sum and a maximum. A very important aspect of this problem is to find a best compromise solution, which is shown to be equivalent to solve the quickest path problem, which has interesting applications in communication and transportation networks. In this paper, we study a special class of bicriterion path problems where the objective functions are defined by a sum and a maximum: The sum-max bicriterion path problem (SMBPP). After reviewing some special kinds of efficient paths, we propose some algorithms to generate these kinds of efficient paths, based on a progressive reduction of the original network. We analyse its relationship with the quickest path problem (QPP), showing that this is equivalent to the weighted problem associated to the SMBPP, which is also solved by a modification of an algorithm proposed for the QPP. A computational study is presented which shows the superiority of the algorithm proposed in this paper over other existing algorithms to generate the entire set E of efficient paths of the SMBPP.

A discrete long-term location-price problem under the assumption of discriminatory pricing: Formulations and parametric analysis

We consider a competitive location problem in which a new firm has to make decisions on the locations of several new facilities as well as on its price setting in order to maximise profit. Under the assumption of discriminatory prices, competing firms set a specific price for each market area. The customers buy one unit of a single homogeneous price-inelastic product from the facility that offers the lowest price in the area the consumers belong to. Three customer choice rules are considered in order to break ties in the offered prices. We prove that, considering long-term competition on price, this problem can be reduced to a problem with decisions on location only. For each one of the choice rules the location problem is formulated as an integer programming model and a parametric analysis of these models is given. To conclude, an application with real data is presented.

Clofarabine‐based chemotherapy for relapsed/refractory adult acute lymphoblastic leukemia and lymphoblastic lymphoma. The Spanish experience

The present study reports the Spanish PETHEMA group experience in 31 heavily pretreated relapsed/refractory acute lymphoblastic leukemia (ALL) and lymphoma (LL) patients treated with clofarabine-based regimens. The complete remission (CR) rate was 31% (median CR duration of 3 months [range 2–28]) and the overall survival probability at 1 year was 10% (95%CI 4–16%). Responses were seen in B and T lineage diseases and in patients with adverse cytogenetics. Hematological and infectious grade >3 toxicities were found in 100 and 67% of the patients, respectively, with 7 (23%) treatment-related deaths. Other organ toxicities were infrequent. Clofarabine-based chemotherapy regimens might induce CRs in ALL and LL patients, but hematological toxicity and infections may limit their use in heavily pretreated patients.

Impact of prior rituximab on outcomes of autologous stem-cell transplantation in patients with relapsed or refractory aggressive B-cell lymphoma: a multicentre retrospective Spanish group of lymphoma/autologous bone marrow transplant study.

The use of highly effective rituximab‐containing therapy for treating diffuse large B‐cell lymphoma (DLBCL) makes it more difficult to salvage relapsed or refractory patients. Autologous stem‐cell transplantation (ASCT) is the reference treatment for these patients, but the impact of previous exposure to rituximab on the subsequent results of ASCT remains unknown. We analysed 248 patients with relapsed or refractory DLBCL or grade 3B follicular lymphoma pre‐treated with rituximab as part of first‐line therapy (R+ group) who received ASCT, in comparison with a control group of 127 patients without previous exposure to rituximab (R− group). The complete remission (CR) rates were similar in both groups. Multivariate analysis identified age‐adjusted International Prognostic Index at diagnosis, extranodal involvement and disease status at transplant, and the number of previous chemotherapy lines as independent factors with a negative influence on CR rate. Compared with R− patients, those in the R+ group had a significantly better progression‐free survival (63% vs. 48% at 5 years) and overall survival (72% vs. 61% at 5 years). This observation was independent of other prognostic factors that affected these outcomes. In conclusion, ASCT is no less effective in patients with relapsed or refractory aggressive B‐cell lymphoma pre‐treated with first‐line rituximab‐containing therapy than in rituximab‐naive patients.

GASUB: finding global optima to discrete location problems by a genetic-like algorithm

In many discrete location problems, a given number s of facility locations must be selected from a set of m potential locations, so as to optimize a predetermined fitness function. Most of such problems can be formulated as integer linear optimization problems, but the standard optimizers only are able to find one global optimum. We propose a new genetic-like algorithm, GASUB, which is able to find a predetermined number of global optima, if they exist, for a variety of discrete location problems. In this paper, a performance evaluation of GASUB in terms of its effectiveness (for finding optimal solutions) and efficiency (computational cost) is carried out. GASUB is also compared to MSH, a multi-start substitution method widely used for location problems. Computational experiments with three types of discrete location problems show that GASUB obtains better solutions than MSH. Furthermore, the proposed algorithm finds global optima in all tested problems, which is shown by solving those problems by Xpress-MP, an integer linear programing optimizer (21). Results from testing GASUB with a set of known test problems are also provided.

A Heuristic Procedure For Path Location With Multisource Demand

Abstract In this paper we present a lower bound for a path location problem with multisource demand based upon the Lagrangian relaxation of a binary integer formulation. Feasible solutions are obtained from the optima of the relaxed subproblems, the best being the heuristic solution. The correctness of the method is only guaranteed when the underlying graph is acyclic. Nevertheless, when the approach is tested by means of a computational study, near-optimum solutions for instances based on acyclic graphs with up to 200 nodes and 700 arcs and cyclic graphs with up to 100 nodes and 780 arcs are found in a few seconds

Profit maximization and reduction of the cannibalization effect in chain expansion

We consider the facility location problem for an expanding chain which competes with other chains offering the same goods or service in a geographical area. Customers are supposed to select the facility with maximum utility to be served and facilities in the expanding chain may have different owners. We first use the weighted method to develop an integer linear programming model to obtain Pareto optimal locations related to the inner competition between the owners of the old facilities and the owners of the new facilities. This model is applied to maximizing the profit of the expanding chain taking into account the loss in market share of its old facilities caused by the entering of new facilities (cannibalization effect). A study with data of Spanish municipalities shows that the cannibalization effect can be significantly reduced by sacrificing a small portion of profit.

Finding multiple global optima for unconstrained discrete location problems

We consider a class of problems where a given number p of facility locations must be selected from a set of s potential locations so as to optimize a pre-determined fitness function. There exist outstanding location problems in this class, such as the p-median, max-covering, MAXCAP, and MAXPROFIT problems. These location problems may contain more than a single global optimal solution. Obtaining multiple global optimal solutions allows us to consider other characteristics in the process of selecting the preferred solution. In [B. Pelegrín, J. Redondo, P. Fernández, I. García, and P. Ortigosa, GASUB: Finding global optima to discrete location problems by a genetic-like algorithm, J. Glob. Optim. 38 (2007), pp. 249–264], a new ‘multimodal’ algorithm (gasub) was presented for solving the previously mentioned location problems. In the paper, the algorithm was fine-tuned to obtain a single global optimum (with 100% success) as fast as possible, and it was compared with two widely used techniques, that is, the standard optimizer Xpress-MP [Xpress-MP, Dashoptimization, 2004.] and the Multi Start Heuristic. In this paper, we propose a new set of parameter values so that gasub can explore the space more deeply and consequently find several alternative global optimal solutions. Moreover, two coarse-grain parallelizations of gasub are presented, cggasub and cggasub_mo. cggasub is able to reduce the computational time of gasub where solutions of the same quality are generated, while cggasub_mo finds more alternative global optima than the sequential version and spending similar computational time in the process. gasub, with the new parameter setting and also the parallel algorithms, will be evaluated using a comprehensive computational set of experiments. Additionally, some criteria can also be used to select one of the known global optimal solutions when several alternatives optimize the corresponding objective function.

The maximum capacity shortest path problem : generation of efficient solution sets

Individual items of flow in a telecommunications or a transportation network may need to be separated by a minimum distance or time, called a “headway”. If link dependent, such restrictions in general have the effect that the minimum time path for a “convoy” of items to travel from a given origin to a given destination will depend on the size of the convoy. The Quickest Path problem seeks a path to minimise this convoy travel time. A closely related bicriterion problem is the Maximum Capacity Shortest Path problem. For this latter problem, an effective implementation is devised for an algorithm to determine desired sets of efficient solutions which in turn facilitates the search for a “best” compromise solution. Numerical experience with the algorithm is reported.