On a problem of Alfréd Rényi

Alfréd Rényi, in a paper of 1962, A new approach to the theory ofEngel's series, proposed a problem related to the growth of theelements of an Engel's series. In this paper, we reformulate andsolve Rényi's problem for both, Engel's series and Pierceexpansions.

On certain greedoid polyhedra, partially indexable scheduling problems and extended restless bandit allocation indices

We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid(whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then theproblem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.

The P-median problem in a changing network: The case of Barcelona

In this paper a p--median--like model is formulated to address theissue of locating new facilities when there is uncertainty. Severalpossible future scenarios with respect to demand and/or the travel times/distanceparameters are presented. The planner will want a strategy of positioning thatwill do as ``well as possible'' over the future scenarios. This paper presents a discrete location model formulation to address this P--Medianproblem under uncertainty. The model is applied to the location of firestations in Barcelona.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Locating emergency services with different priorities: The priority queuing covering location problem

Previous covering models for emergency service consider all the calls to be of the sameimportance and impose the same waiting time constraints independently of the service's priority.This type of constraint is clearly inappropriate in many contexts. For example, in urban medicalemergency services, calls that involve danger to human life deserve higher priority over calls formore routine incidents. A realistic model in such a context should allow prioritizing the calls forservice.In this paper a covering model which considers different priority levels is formulated andsolved. The model heritages its formulation from previous research on Maximum CoverageModels and incorporates results from Queuing Theory, in particular Priority Queuing. Theadditional complexity incorporated in the model justifies the use of a heuristic procedure.

On the drivers of commodity co-movement: Evidence from biofuels

We use the recent introduction of biofuels to study the effect of industry factors on the relationshipsbetween wholesale commodity prices. Correlations between agricultural products and oilare strongest in the 2005-09 period, coinciding with the boom of biofuels, and remain substantialuntil 2011. We disentangle three possible drivers for the linkage: substitution, energy costs, andfinancialization. The timing and magnitude of the biofuels-to-oil relationships are different to thoseof other commodities, and far higher than can be justified by costs and financialization. Substitutionand costs drive the monthly correlations of long-term futures, and each of the three contributeequally to the daily co-movement of the short-term ones. The findings survive many robustnesschecks and appear in the stock market.

Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Drivers and sources of supply flexibility: An exploratory study

Purpose - There has been much research on manufacturing flexibility, but supply chain flexibility is still an under-investigated area. This paper focuses on supply flexibility, the aspects of flexibility related to the upstream supply chain. Our purpose is to investigate why and how firms increase supply flexibility.Methodology/Approach An exploratory multiple case study was conducted. We analyzed seven Spanish manufacturers from different sectors (automotive, apparel, electronics and electrical equipment).Findings - The results show that there are some major reasons why firms need supply flexibility (manufacturing schedule fluctuations, JIT purchasing, manufacturing slack capacity, low level of parts commonality, demand volatility, demand seasonality and forecast accuracy), and that companies increase this type of flexibility by implementing two main strategies: to increase suppliers responsiveness capability and flexible sourcing . The results also suggest that the supply flexibility strategy selected depends on two factors: the supplier searching and switching costs and the type of uncertainty (mix, volume or delivery).Research limitations - This paper has some limitations common to all case studies, such as the subjectivity of the analysis, and the questionable generalizability of results (since the sample of firms is not statistically significant).Implications - Our study contributes to the existing literature by empirically investigating which are the main reasons for companies needing to increase supply flexibility, how they increase this flexibility, and suggesting some factors that could influence the selection of a particular supply flexibility strategy.

Gazelle companies: Growth drivers and an evolution analysis

Gazelle companies are relevant because they generate much more employment than other companies and deliver high returns to their shareholders. This paper analyzes their behavior in the years of high growth and their evolution in the following years. The main factors that explain their success are competitive advantages based on human resources, innovation, internationalization, the excellence in processes and a conservative financial policy. Nevertheless, as time goes by they can be divided in two groups: a group which continues having growth, but most of them with lower growth rates; and the rest which face great problems or even disappear. The present study identifies several key factors that explain this different evolution.

The struggle against creative accounting: Is "true and fair view" part of the problem or part of the solution?

Creative accounting is a growing issue of interest in Spain. In this article we argue that the concept true and fair view can limit or promote the use of creative accounting depending upon its interpretation. We review the range of meanings that true and fair view can take at an international level and compare the experience of the United Kingdom with the Australian one by analysing the use of true and fair view to limit creative accounting. Finally, we suggest lines of action to be considered by the Spanish accounting standards-setting institutions.

A new chance-constrained maximum capture location problem

The paper presents a new model based on the basic Maximum Capture model,MAXCAP. The New Chance Constrained Maximum Capture modelintroduces astochastic threshold constraint, which recognises the fact that a facilitycan be open only if a minimum level of demand is captured. A metaheuristicbased on MAX MIN ANT system and TABU search procedure is presented tosolve the model. This is the first time that the MAX MIN ANT system isadapted to solve a location problem. Computational experience and anapplication to 55 node network are also presented.

Inventory-routing model, for a multi-period problem with stochastic and deterministic demand

The need for integration in the supply chain management leads us to considerthe coordination of two logistic planning functions: transportation andinventory. The coordination of these activities can be an extremely importantsource of competitive advantage in the supply chain management. The battle forcost reduction can pass through the equilibrium of transportation versusinventory managing costs. In this work, we study the specific case of aninventory-routing problem for a week planning period with different types ofdemand. A heuristic methodology, based on the Iterated Local Search, isproposed to solve the Multi-Period Inventory Routing Problem with stochasticand deterministic demand.