Markov decisions in urban modelling

AbstractIn urban fire departments, fire companies are dispatched to respond to alarms which occur spatially and temporally in a generally unpredictable way. Also, the time during which one of the responding units is busy on a call, and hence unavailable to other alarms, is itself a random variable. This variability in demand and service time makes it difficult to maintain a balance between the need for effective response to alarms which occur now and those which may arrive in the future. In this paper, we discuss two specific mathematical models, based on work done by the Rand Institute in New York City, for determining not only how many but also which of the available fire-fighting units to deploy to any given alarm. Each is a Markovian decision model in which the conflicting objectives of adequate response to present or future incidents are explicity accounted for. Similar considerations are applicable to other municipal emergency services

On infinite-dimensional convex programs

AbstractOne way to approach infinite-dimensional nonlinear programs is to append increasingly large cost or penalty terms to the objective function in such a way that the minima of the augmented but unconstrained functions converge to the constrained minimum in the limit. In this paper we establish the convergence of the penalty argument on reflexive B-spaces, and then apply it to obtain the Kuhn-Tucker necessary conditions for convex programs in Hillbert space. The proof is constructive and suggests a computationally feasible algorithm for solving such programs

Using Simulation to Assess the Opportunities of Dynamic Waste Collection

In this paper, we illustrate the use of discrete event simulation to evaluate how dynamic planning methodologies can be best applied for the collection of waste from underground containers. We present a case study that took place at the waste collection company Twente Milieu, located in The Netherlands. Even though the underground containers are already equipped with motion sensors, the planning of container emptying’s is still based on static cyclic schedules. It is expected that the use of a dynamic planning methodology, that employs sensor information, will result in a more efficient collection process with respect to customer satisfaction, profits, and CO2 emissions. In this research we use simulation to (i) evaluate the current planning methodology, (ii) evaluate various dynamic planning possibilities, (iii) quantify the benefits of switching to a dynamic collection process, and (iv) quantify the benefits of investing in fill‐level sensors. After simulating all scenarios, we conclude that major improvements can be achieved, both with respect to logistical costs as well as customer satisfaction

A case of staphylococcal enterocolitis caused by methicillin resistant Staphylococcus aureus

Recently, the frequency of methicillin resistant Staphylococcus aureus (MRSA) infection has been increasing. We experienced a case of postoperative enterocolitis due to MRSA. The patient was an 81-year-old male with benign prostatic hypertrophy. Urine leakage from the penrose drain tube appeared 1 day after suprapubic prostatectomy. We had used intravenous infusion of antibiotic agents including cefodizine (CDZM), imipenem (IPM/CS) and cefmetazol (CMZ). He developed severe diarrhea, high fever, oliguria, leg edema and ascites 24 days after the operation. MRSA was detected from his feces. Toxic shock syndrome toxin-I (TSST-I) was produced by this bacteria the coagulase type of which was type II. The patient was treated with oral vancomycin (1 g/day), to which this bacteria showed sensitivity and the patient showed, improvement, including symptoms, leucocytosis and serum CRP level 12 days after administration of vancomycin