The locomotive assignment problem: a survey on optimization models

The objective of the locomotive assignment problem (LAP) is to assign a fleet of locomotives to a set of trains while satisfying a rich set of operational and budget constraints and optimizing one or more crucial objectives. This paper presents a survey on optimization models for this class of scheduling problems. Depending on the context of application, the kind of model used to solve the LAP varies; accordingly, this influences the solution methodology and algorithms used. In this paper, we review and also suggest a classification of the various models.     

Formulations for an inventory routing problem

In this paper, we present and compare formulations for the inventory routing problem (IRP) where the demand of customers has to be served, over a discrete time horizon, by capacitated vehicles starting and ending their routes at a depot. The objective of the IRP is the minimization of the sum of inventory and transportation costs. The formulations include known and new mathematical programming formulations. Valid inequalities are also presented. The formulations are tested on a large set of benchmark instances. One of the most significant conclusions is that the formulations that use vehicle‐indexed variables are superior to the more compact, aggregate formulations.     

The undirected capacitated arc routing problem with profits

A profit and a demand are associated with each edge of a set of profitable edges of a given graph. A travel time is associated with each edge of the graph. A fleet of capacitated vehicles is given to serve the profitable edges. A maximum duration of the route of each vehicle is also given. The profit of an edge can be collected by one vehicle only that also serves the demand of the edge. The objective of this problem, which is called the undirected capacitated arc routing problem with profits (UCARPP), is to find a set of routes that satisfy the constraints on the duration of the route and on the capacity of the vehicle and maximize the total collected profit. We propose a branch-and-price algorithm and several heuristics. We can solve exactly instances with up to 97 profitable edges. The best heuristics find the optimal solution on most of instances where it is available.     

Analysis of the maximum level policy in a production-distribution system

We consider a production-distribution system, where a facility produces one commodity which is distributed to a set of retailers by a fleet of vehicles. Each retailer defines a maximum level of the inventory. The production policy, the retailers replenishment policies and the transportation policy have to be determined so as to minimize the total system cost. The overall cost is composed by fixed and variable production costs at the facility, inventory costs at both facility and retailers and routing costs. We study two different types of replenishment policies. The well-known order-up to level (OU) policy, where the quantity shipped to each retailer is such that the level of its inventory reaches the maximum level, and the maximum level (ML) policy, where the quantity shipped to each retailer is such that the inventory is not greater than the maximum level. We first show that when the transportation is outsourced, the problem with OU policy is NP-hard, whereas there exists a class of instances where the problem with ML policy can be solved in polynomial time. We also show the worst-case performance of the OU policy with respect to the more flexible ML policy. Then, we focus on the ML policy and the design of a hybrid heuristic. We also present an exact algorithm for the solution of the problem with one vehicle. Results of computational experiments carried out on small size instances show that the heuristic can produce high quality solutions in a very short amount of time. Results obtained on a large set of randomly generated problem instances are also shown, aimed at comparing the two policies.     

Models and Simulations for Portfolio Rebalancing

In 1950 Markowitz first formalized the portfolio optimization problem in terms of mean return and variance. Since then, the mean-variance model has played a crucial role in single-period portfolio optimization theory and practice. In this paper we study the optimal portfolio selection problem in a multi-period framework, by considering fixed and proportional transaction costs and evaluating how much they affect a re-investment strategy. Specifically, we modify the single-period portfolio optimization model, based on the Conditional Value at Risk (CVaR) as measure of risk, to introduce portfolio rebalancing. The aim is to provide investors and financial institutions with an effective tool to better exploit new information made available by the market. We then suggest a procedure to use the proposed optimization model in a multi-period framework. Extensive computational results based on different historical data sets from German Stock Exchange Market (XETRA) are presented.     

An exact approach for portfolio selection with transaction costs and rounds

We consider a single-period mean-safety portfolio selection problem with transaction costs and integer constraints on the quantities selected for the securities (rounds). We propose an exact approach based on the partition of the initial problem into two subproblems and the use of a simple local search heuristic to obtain an initial solution. To the best of our knowledge, no optimal algorithms have been proposed in the literature for this problem. The proposed approach is simple, general and easily adaptable to other problems. An extensive experimental analysis based on real data from the main international Stock Exchange Markets is performed. The results show, on average, an impressive improvement with respect to the computational time and space memory required by CPLEX 7.0. We also show that the solution of the first subproblem can be used on its own as an extremely effective heuristic.     

Changes of the cell surface hydrophobicity of Lactobacillus acidophilus La‐5 in response to pH,temperature and inulin

The main topic of this study was to study how cell surface hydrophobicity (CSH) could change in response to pH, temperature and inulin; Lactobacillus acidophilus La‐5 was used as a model microorganism. pH, temperature, inulin and incubation time (exposure to prebiotic or incubation at pH 4.0 and 9.0) were combined through a full factorial design and a Central Composite Design; the results were analysed using a multifactorial anova (first step) and a stepwise regression (second step). Temperature and pH significantly affected CSH: an increase in the temperature determined a significant increase in CSH, whereas the correlation pH vs. CSH was negative, as an increase in pH caused a significant decrease in CSH. Inulin played a significant role, but its effect could be influenced by temperature, pH and exposure time. This study is the first approach on the effects of some environmental factors on CSH and suggests that the culturing conditions and/or the exposure to some prebiotics could modify it with positive or negative effects.     

A comparison of higher order auditory processes in younger and older adults.

The authors conducted 3 experiments investigating the effects of aging on higher order auditory processes. They compared younger and older adults with respect to (a) their auditory channel capacity, (b) the extent of their top-down control over auditory gain, and (c) their ability to focus attention on a narrow band of frequencies. To ensure that subclinical cochlear processing deficits in older adults (e.g., higher thresholds, poorer discrimination of frequency and intensity differences) did not limit performance, the authors used only stimuli that were perfectly discriminable by all participants. No age differences were found in any of these experiments, suggesting that some higher order auditory processes (e.g., top-down control over auditory gain, auditory attention) are preserved in normal aging, despite numerous age-related declines in peripheral auditory functionality. (PsycINFO Database Record (c) 2010 APA, all rights reserved)