How do different densities in a network affect the optimal location of service centers?

The p-median problem is often used to locate p service centers by minimizing their distances to a geographically distributed demand (n). The optimal locations are sensitive to geographical context such as road network and demand points especially when they are asymmetrically distributed in the plane. Most studies focus on evaluating performances of the p-median model when p and n vary. To our knowledge this is not a very well-studied problem when the road network is alternated especially when it is applied in a real world context. The aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the density in the road network is alternated. The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 service centers we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000. To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when nodes in the road network increase and p is low. When p is high the improvements are larger. The results also show that choice of the best network depends on p. The larger p the larger density of the network is needed. 

Acupuncture for labour pain

Background: Acupuncture involves puncturing the skin with thin sterile needles at defined acupuncture points. Previous studies are inconclusive regarding the effect of acupuncture on labour pain, but some studies have found a reduction in the use of pharmacological pain relief when acupuncture is administered. The appropriate dose of acupuncture treatment required to elicit a potential effect on labour pain has not been fully explored. The dose is determined by many different factors, including the number of needles used and the intensity of the stimulation. In Sweden, manual stimulation of the needles is common practice when acupuncture is used for labour pain, but electrical stimulation of the needles, which gives a higher dose, could possibly be more effective. The overall aim of this thesis was to evaluate the effectiveness of acupuncture with manual stimulation (MA) of the needles as well as acupuncture with a combination of manual and electrical stimulation (EA) in reducing labour pain, compared with standard care without any form of acupuncture (SC). Methods: The study was designed as a three-armed randomised controlled trial in which 303 nulliparous women with normal pregnancies were randomised to MA, EA, or SC. The primary outcome was labour pain, assessed using the Visual Analogue Scale (VAS). Secondary outcomes were relaxation during labour, use of obstetric pain relief, and associations between maternal characteristics and labour pain and use of epidural analgesia respectively. Also, labour and infant outcomes, recollection of labour pain, and maternal experiences, such as birth experience and experience of the midwife, were investigated two months after the birth. The sample size calculation was based on the potential to discover a difference of 15 mm on the VAS. Data were collected during labour before the interventions, the day after birth, and two months later. Besides using the VAS, information was collected by means of study specific protocol, questionnaires and medical records. Results: The mean VAS scores were 66.4 in the MA group, 68.5 in the EA group, and 69.0 in the SC group (mean differences: MA vs. SC 2.6 95% CI -1.7 to 6.9, and EA vs. SC 0.6 95% CI -3.6 to 4.8). Other methods of pain relief were used less frequently in the EA group, including epidural analgesia, MA 61.4%, EA 46%, and SC 69.9%. (EA vs. SC OR 0.4 95% CI 0.2 to 0.7). No statistically significant differences were found in the recollection of labour pain between the three groups two months after birth (mean VAS score: MA 69.3, EA 68.7 and SC 70.1). A few maternal characteristics were associated with labour pain (age, dysmenorrhea, and cervix dilatation), but none of the investigated characteristics predicted the outcome of the acupuncture treatment in MA or EA. Women in the EA group experienced acupuncture as being effective for labour pain to a higher extent than women who received MA, MA 44.4%, EA 67.1% (EA vs. MA OR 2.4 95% CI 1.2 to 4.8). Women in the EA group also spent less time in labour (mean 500 min) than those who received MA (mean 619 min) and SC (mean 615 min) (EA vs. MA HR 1.4 95% CI 1.0 to1.9, EA vs. SC HR 1.4, 95% CI 1.1 to 2.0), and had less blood loss than women receiving SC, (EA vs. SC OR 0.1 95% CI 0.3 to 0.7). The women’s assessment of the midwife as being supportive during labour (MA 77.2%, EA 83.5%, SC 80%), overall satisfaction with midwife care (MA 100%, EA 97.5%, SC 98.7%), and having an overall positive childbirth experience (MA 64.6%, EA 61.0%, SC 54.3%) did not differ statistically. No serious side effects of the acupuncture treatment were reported. Conclusion: Acupuncture, regardless of type of stimulation, did not differ from standard care without acupuncture in terms of reducing women’s experience of pain during labour, or their memory of pain and childbirth overall two months after the birth. However, other forms of obstetric pain relief were less frequent in women receiving a combination of manual and electrical stimulation, suggesting that this method could facilitate coping with labour pain.

How does data quality in a network affect heuristic solutions?

To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.