A mixed-integer linear programming approach to the optimization of event-bus schedules: a scheduling application in the tourism sector

This paper deals with “The Enchanted Journey,” which is a daily event tour booked by Bollywood-film fans. During the tour, the participants visit original sites of famous Bollywood films at various locations in Switzerland; moreover, the tour includes stops for lunch and shopping. Each day, up to five buses operate the tour. For operational reasons, however, two or more buses cannot stay at the same location simultaneously. Further operative constraints include time windows for all activities and precedence constraints between some activities. The planning problem is how to compute a feasible schedule for each bus. We implement a two-step hierarchical approach. In the first step, we minimize the total waiting time; in the second step, we minimize the total travel time of all buses. We present a basic formulation of this problem as a mixed-integer linear program. We enhance this basic formulation by symmetry-breaking constraints, which reduces the search space without loss of generality. We report on computational results obtained with the Gurobi Solver. Our numerical results show that all relevant problem instances can be solved using the basic formulation within reasonable CPU time, and that the symmetry-breaking constraints reduce that CPU time considerably.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

Fetal programming and epigenetic mechanisms in arterial hypertension.

PURPOSE OF REVIEW To provide an overview of available evidence of the potential role of epigenetics in the pathogenesis of hypertension and vascular dysfunction. RECENT FINDINGS Arterial hypertension is a highly heritable condition. Surprisingly, however, genetic variants only explain a tiny fraction of the phenotypic variation and the term 'missing heritability' has been coined to describe this phenomenon. Recent evidence suggests that phenotypic alteration that is unrelated to changes in DNA sequence (thereby escaping detection by classic genetic methodology) offers a potential explanation. Here, we present some basic information on epigenetics and review recent work consistent with the hypothesis of epigenetically induced arterial hypertension. SUMMARY New technologies that enable the rigorous assessment of epigenetic changes and their phenotypic consequences may provide the basis for explaining the missing heritability of arterial hypertension and offer new possibilities for treatment and/or prevention.

SOMS: SurrOgate MultiStart algorithm for use with nonlinear programming for global optimization

SOMS is a general surrogate-based multistart algorithm, which is used in combination with any local optimizer to find global optima for computationally expensive functions with multiple local minima. SOMS differs from previous multistart methods in that a surrogate approximation is used by the multistart algorithm to help reduce the number of function evaluations necessary to identify the most promising points from which to start each nonlinear programming local search. SOMS’s numerical results are compared with four well-known methods, namely, Multi-Level Single Linkage (MLSL), MATLAB’s MultiStart, MATLAB’s GlobalSearch, and GLOBAL. In addition, we propose a class of wavy test functions that mimic the wavy nature of objective functions arising in many black-box simulations. Extensive comparisons of algorithms on the wavy testfunctions and on earlier standard global-optimization test functions are done for a total of 19 different test problems. The numerical results indicate that SOMS performs favorably in comparison to alternative methods and does especially well on wavy functions when the number of function evaluations allowed is limited.

Developmental programming of tumor suppressor gene penetrance

Epidemiological studies have led to the hypothesis that major risk factors for developing diseases such as hypertension, cardiovascular disease and adult-onset diabetes are established during development. This developmental programming hypothesis proposes that exposure to an adverse stimulus or insult at critical, sensitive periods of development can induce permanent alterations in normal physiological processes that lead to increased disease risk later in life. For cancer, inheritance of a tumor suppressor gene defect confers a high relative risk for disease development. However, these defects are rarely 100% penetrant. Traditionally, gene-environment interactions are thought to contribute to the penetrance of tumor suppressor gene defects by facilitating or inhibiting the acquisition of additional somatic mutations required for tumorigenesis. The studies presented herein identify developmental programming as a distinctive type of gene-environment interaction that can enhance the penetrance of a tumor suppressor gene defect in adult life. Using rats predisposed to uterine leiomyoma due to a germ-line defect in one allele of the tuberous sclerosis complex 2 (Tsc-2) tumor suppressor gene, these studies show that early-life exposure to the xenoestrogen, diethylstilbestrol (DES), during development of the uterus increased tumor incidence, multiplicity and size in genetically predisposed animals, but failed to induce tumors in wild-type rats. Uterine leiomyomas are ovarian-hormone dependent tumors that develop from the uterine myometrium. DES exposure was shown to developmentally program the myometrium, causing increased expression of estrogen-responsive genes prior to the onset of tumors. Loss of function of the normal Tsc-2 allele remained the rate-limiting event for tumorigenesis; however, tumors that developed in exposed animals displayed an enhanced proliferative response to ovarian steroid hormones relative to tumors that developed in unexposed animals. Furthermore, the studies presented herein identify developmental periods during which target tissues are maximally susceptible to developmental programming. These data suggest that exposure to environmental factors during critical periods of development can permanently alter normal physiological tissue responses and thus lead to increased disease risk in genetically susceptible individuals. ^