Potentiometric determination of nickel (II) with sodium diethyldithiocarbamate (NaDEDC)

The article presents the results of potentiometric titration of the solution containing Ni (II) by the solution of sodium diethylditheocarbamate (NaDEDC). The possibilities of carbon composite electrode (CCE) and certain ion-selective and metal electrodes as the sensors for potentiometric determination of ions were investigated. The conditions for potentiometric titration of nickel (reagent, pH, composition of supporting solution, efficient electrode, effect of interfering ions) using sensors have been studied and optimized. The titration curves were processed by the linearization method which provide determination of equivalence point with high accuracy

The distributed p-median problem in computer networks

Many distributed services in computer networks rely on a set of active facilities that are selected among a potentially large number of candidates. The active facilities then contribute and cooperate to deliver a specific service to the users of the distributed system. In this scenario graph partitioning or clustering is often adopted to determine the most efficient locations of the facilities. The identification of the optimal set of facility locations is known as the p-median problem in networks, is NP-hard and is typically solved by using heuristic methods. The goal is to select p locations among all candidate network nodes such that some cost function is minimised. A typical example of such a function is the overall communication cost to deliver the service to the users of the distributed system. Locating facilities in near-optimal locations has been extensively studied for different application domains. Most of these studies have investigated sequential algorithms and centralised approaches. However, centralised approaches are practically infeasible in large-scale and dynamic networks, where the problem is inherently distributed or because of the large communication overhead and memory requirements for gathering complete information about the network topology and the users. In this work distributed approaches to the p-median problem are investigated. Two solutions are proposed for addressing the facility locations problem in a fully distributed environment. Two different iterative heuristic approaches are applied to gradually improve a random initial solution and to converge to a final solution with a local minimum of the overall cost. While the first approach adopts a fine granularity by identifying a single change to improve the solution at each iteration, the second approach applies changes to every component of the solution at each iteration. An experimental comparative analysis based on simulations has shown that the approach with a finer granularity is able to deliver a better optimisation of the overall cost with longer convergence time. Both approaches have excellent scalability and provide an effective tool to optimise the facility locations from within the network. No prior knowledge of the system is required, no data needs to be gathered in a centralised server and the same process is used to identify and to deploy the facility locations solution in the network since the process is fully decentralised

LOCATION OF MULTIPLE SERVER COMMON SERVICE CENTERS OR PUBLIC FACILITIES FOR MINIMIZING GENERAL CONGESTION AND TRAVEL COST FUNCTIONS

We propose a model and solution methods, for locating a fixed number of multiple-server, congestible common service centers or congestible public facilities. Locations are chosen so to minimize consumers ’ congestion (or queuing) and travel costs, considering that all the demand must be served. Customers choose the facilities to which they travel in order to receive service at minimum travel and congestion cost. As a proxy for this criterion, total travel and waiting costs are minimized. The travel cost is a general function of the origin and destination of the demand, while the congestion cost is a general function of the number of customers in queue at the facilities

Joint location-inventory problem with differentiated service levels using critical level policy

Artículo de publicación ISIThis paper analyzes the design of a distribution network for fast-moving items able to provide differentiated service levels in terms of product availability for two demand classes (high and low priority) using a critical level policy. The model is formulated as a MINLP with chance constraints for which we propose a heuristic to solve it. Although the heuristic does not guarantee an optimal solution, our computational experiments have shown that it provides good-quality solutions that are on average 0.8% and at worst 2.7% from the optimal solution.Institute Complex Engineering Systems ICM-MINECON P-05-004-F CONICYT FBO1

On the effect of inventory policies on distribution network design with several demand classes

This paper studies the effect of several inventory policies on the design of a distribution network for fast-moving items able to provide differentiated service levels in terms of product availability for several demand classes. We consider the distribution network design problem when the global round-up, single class allocation, local separate stock, local round-up, and critical level inventory policies are used. We show how to formulate these problems as conic quadratic mixed-integer problems and prove that the critical level policy provides the lowest cost distribution network design. Further results and a computational study show how these different models compare in practice.Complex Engineering Systems Institute, CONICYT-PIA-FB081