Penerapan Metode Saving Matrix untuk Meminimumkan Biaya Distribusi (Studi Kasus: Toko Oleh-Oleh Surabaya Honest)

Toko oleh-oleh Surabaya Honest merupakan usaha kecil menengah yang memproduksi berbagai jenis roti. Dalam mendistribusikan produknya, rute yang harus ditempuh dibagi menjadi 5 jalur pengiriman yaitu Sedati, Buncitan, Mangkurejo, Rungkut, dan Wadung Asri. Toko oleh-oleh Surabaya Honest masih mengalami kesulitan dalam menentukan rute distribusi roti dikarenakan jarak antara tempat produksi dengan outlet saling berjauhan dan sampai saat ini belum memiliki metode khusus dalam menentukan rute distribusi. Oleh karena itu, penelitian ini bertujuan untuk menentukan rute pengiriman yang akan ditempuh sehingga dapat meminimalkan biaya distribusi pada Toko oleh-oleh Surabaya Honest. Penentuan rute transportasi ini diselesaikan dengan metode Saving Matriks. Metode tersebut digunakan dalam menentukan rute pengiriman produk ke wilayah-wilayah outlet dengan cara menentukan rute pengiriman yang akan dilalui dan jumlah kapasitas kendaraan agar bisa memperoleh rute terpendek dan biaya distribusi yang minim. Perbandingan rute pengiriman produk Toko oleh-oleh Surabaya Honest dengan menggunakan metode saving matrix dan metode nearest neighbor menghasilkan rute yang efektif dan efisien dimana rute awal sebanyak 4 rute menjadi 2 rute baru. Dengan diterapkannya metode saving matrix menunjukkan penurunan jarak tempuh pengiriman yang semula 120,7 km menjadi 60,2 km, dengan demikian didapatkan penghematan jarak sebesar 60,5 km. Biaya total distribusi sebelum penerapan metode saving matrix yaitu sebesar Rp. 428.040 dan setelah penerapan metode saving matrix menjadi Rp. 213.370, sehingga perusahaan dapat menghemat Rp. 214.670 atau sebesar 50,15%

Trends in Cancer Mortality in 15 Industrialized Countries, 1969-1986

Background: Assessing trends in cancer provides a means for gauging progress against the disease, estimating future demands for care and treatment, and suggesting clues about shifting causal factors that may account for the more recent changes. Purpose: This study was designed to evaluate trends in the major sites of cancer associated with high mortality rates in 15 industrialized countries. To highlight differences among regions, we grouped these countries into six geographic areas: United States, Eastern Europe, Western Europe, East Asia, Oceania, and Nordic countries. In addition, cancer mortality trends in these regions were compared with incidence patterns in the United States. Methods: Data provided by the World Health Organization were used to evaluate age-specific mortality trends from 1969 through 1986 for lung, breast, prostate, stomach, and colorectal cancers and for all other sites considered as a group. We also assembled and analyzed data from the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute for the same sites and age groups from 1973 through 1986. Results: Over the period 1969 through 1986, recorded cancer mortality in persons aged 45 years and older in the six regions studied has increased for lung, breast, and prostate cancers in most age groups, while the decline in stomach cancer mortality is substantial. The increase in lung cancer deaths in men aged 45-54 years has slowed greatly or reversed in all areas except Eastern Europe and East Asia. Trends for intestinal cancer vary by age and region. For all other sites considered as a group, increases have occurred for persons older than 64 years in most regions. In Eastern Europe, there are disturbingly high rates and rapid increases for several of the major forms of cancer in persons aged 45-54 years. In general, trends for cancer incidence in the United States parallel those for mortality. For intestinal cancer, however, incidence has increased while mortality has declined. Conclusions: The trends we report cannot be explained solely by changes in cigarette smoking or aging. Other causes of changes in cancer incidence and mortality need to be determined. Implications: The increasing and decreasing trends in mortality from and incidence of cancer that we found are important for health care planning and may also suggest opportunities for research in cancer prevention. [J Natl Cancer Inst 84: 313-320, 1992

A survey of solution techniques for the partially observed Markov decision process

We survey several computational procedures for the partially observed Markov decision process (POMDP) that have been developed since the Monahan survey was published in 1982. The POMDP generalizes the standard, completely observed Markov decision process by permitting the possibility that state observations may be noise-corrupted and/or costly. Several computational procedures presented are convergence accelerating variants of, or approximations to, the Smallwood-Sondik algorithm. Finite-memory suboptimal design results are reported, and new research directions involving heuristic search are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44198/1/10479_2005_Article_BF02204836.pd

Cancer-related chronic pain

BACKGROUND: Disparities in cancer survival and pain rates negatively impact quality of life (QOL). This study examines cancer-related chronic pain (CP) and its impact on QOL in diverse cancer survivors. METHODS: This survey study focused on current and past pain, health, and QOL in black and white cancer survivors. Participants with breast, colorectal, lung, and prostate cancer and multiple myeloma were recruited through the Michigan State Cancer Registry. Analysis of variance was used to examine outcome differences by pain status, race, and sex. Hierarchical regressions explored predictors for experiencing pain. RESULTS: The subjects (N = 199) were 31% black, 49% female, and 57 to 79 years old; 19.5% experienced current pain, and 42.6% reported pain since diagnosis. Women experience more pain ( P < .001) and greater pain severity ( P = .04) than men. Blacks experienced more pain interference and disability ( P < .05). Experiencing pain is related to greater depressive symptoms, poorer functioning, and more symptoms. In hierarchical regressions, female sex predicted pain since diagnosis; pain severity for pain since diagnosis was predicted by black race and female sex. CONCLUSIONS: The authors extend the literature by showing that 20% of diverse cancer survivors had cancer-related CP, and 43% had experienced pain since diagnosis, revealing racial and sex disparities in cancer-related CP's incidence and impact on QOL. Having pain was related to poorer QOL in several domains and was more frequently experienced by women. Although black race was not related to pain prevalence, it was related to greater severity. This study reveals an unaddressed cancer survivorship research, clinical, and policy issue. Cancer 2011. © 2010 American Cancer Society.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83753/1/25761_ftp.pd

Medical decision making for patients with Parkinson disease under Average Cost Criterion

Parkinson's disease (PD) is one of the most common disabling neurological disorders and results in substantial burden for patients, their families and the as a whole society in terms of increased health resource use and poor quality of life. For all stages of PD, medication therapy is the preferred medical treatment. The failure of medical regimes to prevent disease progression and to prevent long-term side effects has led to a resurgence of interest in surgical procedures. Partially observable Markov decision models (POMDPs) are a powerful and appropriate technique for decision making. In this paper we applied the model of POMDP's as a supportive tool to clinical decisions for the treatment of patients with Parkinson's disease. The aim of the model was to determine the critical threshold level to perform the surgery in order to minimize the total lifetime costs over a patient's lifetime (where the costs incorporate duration of life, quality of life, and monetary units). Under some reasonable conditions reflecting the practical meaning of the deterioration and based on the various diagnostic observations we find an optimal average cost policy for patients with PD with three deterioration levels

Dynamic Health Policies for Controlling the Spread of Emerging Infections: Influenza as an Example

The recent appearance and spread of novel infectious pathogens provide motivation for using models as tools to guide public health decision-making. Here we describe a modeling approach for developing dynamic health policies that allow for adaptive decision-making as new data become available during an epidemic. In contrast to static health policies which have generally been selected by comparing the performance of a limited number of pre-determined sequences of interventions within simulation or mathematical models, dynamic health policies produce “real-time” recommendations for the choice of the best current intervention based on the observable state of the epidemic. Using cumulative real-time data for disease spread coupled with current information about resource availability, these policies provide recommendations for interventions that optimally utilize available resources to preserve the overall health of the population. We illustrate the design and implementation of a dynamic health policy for the control of a novel strain of influenza, where we assume that two types of intervention may be available during the epidemic: (1) vaccines and antiviral drugs, and (2) transmission reducing measures, such as social distancing or mask use, that may be turned “on” or “off” repeatedly during the course of epidemic. In this example, the optimal dynamic health policy maximizes the overall population's health during the epidemic by specifying at any point of time, based on observable conditions, (1) the number of individuals to vaccinate if vaccines are available, and (2) whether the transmission-reducing intervention should be either employed or removed

Partial observable update for subjective logic and its application for trust estimation

Subjective Logic (SL) is a type of probabilistic logic, which is suitable for reasoning about situations with uncertainty and incomplete knowledge. In recent years, SL has drawn a significant amount of attention from the multi-agent systems community as it connects beliefs and uncertainty in propositions to a rigorous statistical characterization via Dirichlet distributions. However, one serious limitation of SL is that the belief updates are done only based on completely observable evidence. This work extends SL to incorporate belief updates from partially observable evidence. Normally, the belief updates in SL presume that the current evidence for a proposition points to only one of its mutually exclusive attribute states. Instead, this work considers that the current attribute state may not be completely observable, and instead, one is only able to obtain a measurement that is statistically related to this state. In other words, the SL belief is updated based upon the likelihood that one of the attributes was observed. The paper then illustrates properties of the partial observable updates as a function of the state likelihood and illustrates the use of these likelihoods for a trust estimation application. Finally, the utility of the partial observable updates is demonstrated via various simulations including the trust estimation case.U.S. Army Research Laboratory ; U.K. Ministry of Defence ; TÜBİTAKpre-prin