Comparison of the effects of desmopressin and pethedin in treatment of acute renal colic

Background and aim: Renal colic pain is a problem in emergency rooms and for some out- patients. Narcotic drugs are the drugs of choice for pain relief in these patients, but possible abuse, inaccessibility and some complications limit their usage. Recently desmopressin drop has been proposed as an analgesic. This drug is used by nasal route and has physiologic effects for pain relief in renal colic. In this study, we compare the analgesic effects of this drug with pethedin, one of the drugs of choice in renal colic. Methods: Sixty-eight renal colic patients (43 men, 25 women) were randomly divided into two equal groups. The first group was treated with 25 mg intramuscular pethedin and the second group treated with 40 μg intranasal desmopressin. Pain intensity was measured at admission, 10 and 30 minutes after the drug administration with McGill pain questionnaire. Results: Pethedin resulted in a decrease of pain from 12.7±0.6 to10.1±0.5 at 10 minutes and to 2.9±0.5 at 30 minutes after the drug administration. desmopressin caused a decrease of pain from 11.5±2.8 to 10.1±0. 6 at 10 minutes and 9.5±0.5 at 30 minutes after the drug administration. The difference was significant (p<0.01). Conclusion: The results of this study revealed that desmopressin is not effective for pain relief and pethedin is a drug of choice for renal colic

Hub Network Design Problems with Profits

In this thesis we study a new class of hub location problems denoted as \textit{hub network design problems with profits} which share the same feature: a profit oriented objective. We start from a basic model in which only routing and location decisions are involved. We then investigate more realistic models by incorporating new elements such as different types of network design decisions, service commitments constraints, multiple demand levels, multiple capacity levels and pricing decisions. We present mixed-integer programming formulations for each variant and extension and provide insightful computational analyses regarding to their complexity, network topologies and their added value compared to related hub location problems in the literature. Furthermore, we present an exact algorithmic framework to solve two variants of this class of problems. We continue this study by introducing joint hub location and pricing problems in which pricing decisions are incorporated into the decision-making process. We formulate this problem as a mixed-integer bilevel problem and provide feasible solutions using two math-heuristics. The dissertation ends with some conclusions and comments on avenues of future research

Exact solution of hub network design problems with profits

This paper studies hub network design problems with profits. They consider a profit-oriented objective that measure the tradeoff between the revenue due to served commodities and the overall network design and transportation costs. An exact algorithmic framework is proposed for two variants of this class of problems, where a sophisticated Lagrangian function that exploits the structure of the problems is used to efficiently obtain bounds at the nodes of an enumeration tree. In addition, reduction tests and partial enumerations are used to considerably reduce the size of the problems and thus help decrease the computational effort. Numerical results on a set of benchmark instances with up to 100 nodes confirm the efficiency of the proposed algorithmic framework. The proposed methodology can be used as a tool to solve more complex variants of this class of problems as well as other discrete location and network design problems involving servicing decisions.Peer ReviewedPostprint (author's final draft

Design of hybrid multimodal logistic hub network with postponement strategy

This paper aims at suggesting a method allowing to design a logistic hub network in the context of postponement strategy, postponement being performed in hubs having industrial facilities in addition to logistic ones. We propose a two-stage mathematical mixed integer linear programming model for: 1) logistic hub network design 2) postponement location on the designed hub network. The suggested model manages characteristics not yet taken into account simultaneously in the literature: hierarchical logistic structure, postponement strategy, multi-commodity, multi-packaging of goods (raw materials or components vs. final products), multi-period planning. The solutions are compared through services levels and logistic costs

Hub network design problems with profits

This paper presents a class of hub network design problems with profit-oriented objectives, which extend several families of classical hub location problems. Potential applications arise in the design of air and ground transportation networks. These problems include decisions on the origin/destination nodes that will be served as well as the activation of different types of edges, and consider the simultaneous optimization of the collected profit, setup cost of the hub network and transportation cost. Alternative models and integer programming formulations are proposed and analyzed. Results from computational experiments show the complexity of such models and highlight their superiority for decision-making.Peer Reviewe

Hub network design problems with profits

This paper presents a class of hub network design problems with profit-oriented objectives, which extend several families of classical hub location problems. Potential applications arise in the design of air and ground transportation networks. These problems include decisions on the origin/destination nodes that will be served as well as the activation of different types of edges, and consider the simultaneous optimization of the collected profit, setup cost of the hub network and transportation cost. Alternative models and integer programming formulations are proposed and analyzed. Results from computational experiments show the complexity of such models and highlight their superiority for decision-making.Peer Reviewe

Exact solution of hub network design problems with profits

This paper studies hub network design problems with profits. They consider a profit-oriented objective that measure the tradeoff between the revenue due to served commodities and the overall network design and transportation costs. An exact algorithmic framework is proposed for two variants of this class of problems, where a sophisticated Lagrangian function that exploits the structure of the problems is used to efficiently obtain bounds at the nodes of an enumeration tree. In addition, reduction tests and partial enumerations are used to considerably reduce the size of the problems and thus help decrease the computational effort. Numerical results on a set of benchmark instances with up to 100 nodes confirm the efficiency of the proposed algorithmic framework. The proposed methodology can be used as a tool to solve more complex variants of this class of problems as well as other discrete location and network design problems involving servicing decisions.Peer Reviewe