Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems

Identifying the community structure of the international food-trade multi network

Achieving international food security requires improved understanding of how international trade networks connect countries around the world through the import-export flows of food commodities. The properties of food trade networks are still poorly documented, especially from a multi-network perspective. In particular, nothing is known about the community structure of food networks, which is key to understanding how major disruptions or 'shocks' would impact the global food system. Here we find that the individual layers of this network have densely connected trading groups, a consistent characteristic over the period 2001 to 2011. We also fit econometric models to identify social, economic and geographic factors explaining the probability that any two countries are co-present in the same community. Our estimates indicate that the probability of country pairs belonging to the same food trade community depends more on geopolitical and economic factors -- such as geographical proximity and trade agreements co-membership -- than on country economic size and/or income. This is in sharp contrast with what we know about bilateral-trade determinants and suggests that food country communities behave in ways that can be very different from their non-food counterparts.Comment: 47 pages, 19 figure

Optimizing the Efficiency of the United States Organ Allocation System through Region Reorganization

Allocating organs for transplantation has been controversial in the United States for decades. Two main allocation approaches developed in the past are (1) to allocate organs to patients with higher priority at the same locale; (2) to allocate organs to patients with the greatest medical need regardless of their locations. To balance these two allocation preferences, the U.S. organ transplantation and allocation network has lately implemented a three-tier hierarchical allocation system, dividing the U.S. into 11 regions, composed of 59 Organ Procurement Organizations (OPOs). At present, an procured organ is offered first at the local level, and then regionally and nationally. The purpose of allocating organs at the regional level is to increase the likelihood that a donor-recipient match exists, compared to the former allocation approach, and to increase the quality of the match, compared to the latter approach. However, the question of which regional configuration is the most efficient remains unanswered. This dissertation develops several integer programming models to find the most efficient set of regions. Unlike previous efforts, our model addresses efficient region design for the entire hierarchical system given the existing allocation policy. To measure allocation efficiency, we use the intra-regional transplant cardinality. Two estimates are developed in this dissertation. One is a population-based estimate; the other is an estimate based on the situation where there is only one waiting list nationwide. The latter estimate is a refinement of the former one in that it captures the effect of national-level allocation and heterogeneity of clinical and demographic characteristics among donors and patients. To model national-level allocation, we apply a modeling technique similar to spill-and-recapture in the airline fleet assignment problem. A clinically based simulation model is used in this dissertation to estimate several necessary parameters in the analytic model and to verify the optimal regional configuration obtained from the analytic model. The resulting optimal region design problem is a large-scale set-partitioning problem in whichthere are too many columns to handle explicitly. Given this challenge, we adapt branch and price in this dissertation. We develop a mixed-integer programming pricing problem that is both theoretically and practically hard to solve. To alleviate this existing computational difficulty, we apply geographic decomposition to solve many smaller-scale pricing problems based on pre-specified subsets of OPOs instead of a big pricing problem. When solving each smaller-scale pricing problem, we also generate multiple ``promising' regions that are not necessarily optimal to the pricing problem. In addition, we attempt to develop more efficient solutions for the pricing problem by studying alternative formulations and developing strong valid inequalities. The computational studies in this dissertation use clinical data and show that (1) regional reorganization is beneficial; (2) our branch-and-price application is effective in solving the optimal region design problem

Carnivore Competition and Resource use in the Serengeti Ecosystem of Tanzania

Coexisting ungulate-eating carnivores--lion, spotted hyena, cheetah, leopard, African wild dog, black-backed jackal, common jackal, and six species of vulture--are examined in East Africa\u27s Serengeti ecosystem. Niche similarities year-round, by season, and by location are described using food, habitat, time of hunting, and other variables. Intraspecific niches of cheetah sex, age, and social groups show that male coalitions differ most from the others in hunting behavior and habitat use. Tests using the carnivore data failed to support hypotheses about niche breadth variation, niche overlap variation, range of food items, and niche inclusion. Densities of the five largest Carnivora in the 35,500 square kilometer ecosystem are 0.513/sq km; including the two jackals gives a density of 1.55/sq km. Their prey--30 ungulate species--are 84 .85/sq km. Prey and predator ratios suggest that the Serengeti Plains in 1977 had a three-fourths decrease in relative abundance of prey to predators from wet season to dry season . Year-round the Ngorongoro Crater had a prey:predator ratio slightly larger than that of the dry season Serengeti Plains. Literature review suggests that cleptoparasitism and direct killing are very important forms of interference competition among and within carnivore species . Evidence for exploitation competition i s scant, but is inferred because local environments are unpredictable f or carnivores. Analysis of body sizes fails to support the hypothesized ratios of 2.0 for body weigh t and 1.28 for linear dimensions . Three methods of calculating multidimensional niche metrics (product, summation, and projection) are compared. Apparently the Serengeti\u27s carnivores coexist because of their behavioral flexibility in an unpredictable environment . Niche descriptions were of little he l p in assessing the foci for potential and real competition among carnivores . Only the direct observations of interference competition in long-term field studies identified where competitive interactions are occurring with sufficient intensity to provide a numerical response in a population. Spotted hyenas some times competitively exclude African wild dogs locally . Management f or a high abundance and diversity of carnivores probably requires maintaining high densities of prey and varied habitats. Specific recommendations are made for cheetah and African wild dog conservation