Surrogate Assisted Optimisation for Travelling Thief Problems

The travelling thief problem (TTP) is a multi-component optimisation problem involving two interdependent NP-hard components: the travelling salesman problem (TSP) and the knapsack problem (KP). Recent state-of-the-art TTP solvers modify the underlying TSP and KP solutions in an iterative and interleaved fashion. The TSP solution (cyclic tour) is typically changed in a deterministic way, while changes to the KP solution typically involve a random search, effectively resulting in a quasi-meandering exploration of the TTP solution space. Once a plateau is reached, the iterative search of the TTP solution space is restarted by using a new initial TSP tour. We propose to make the search more efficient through an adaptive surrogate model (based on a customised form of Support Vector Regression) that learns the characteristics of initial TSP tours that lead to good TTP solutions. The model is used to filter out non-promising initial TSP tours, in effect reducing the amount of time spent to find a good TTP solution. Experiments on a broad range of benchmark TTP instances indicate that the proposed approach filters out a considerable number of non-promising initial tours, at the cost of omitting only a small number of the best TTP solutions

Thrombotic Thrombocytopenic Purpura, Moschcowitz Syndrome

The authors present a case of a 16-year-old boy, who was referred to the hospital due to thrombocytopenia, anemia, proteinuria and hyperbilirubinemia. Based on the clinical picture and the laboratory data, thrombotic thrombocytopenic purpura (TTP) was diagnosed. The adequate therapy was immediately started. TTP is quite a rare entity. The etiology and the pathogenesis are not well defined. The authors summarize the different pathomechanisms, which may play a role in the development of TTP. Similarity to the hemolytic uremic syndrome (HUS), therapeutic possibilities, prognosis and the outcome are also discussed. The importance of the early diagnosis of TTP in childhood, and life-saving effect of the adequate treatment are emphasized

How I treat thrombotic thrombocytopenic purpura and atypical haemolytic uraemic syndrome

Thrombotic thrombocytopenic purpura (TTP) and atypical haemolytic uraemic syndrome (aHUS) are acute, rare life-threatening thrombotic microangiopathies that require rapid diagnosis and treatment. They are defined by microangiopathic haemolytic anaemia and thrombocytopenia, with renal involvement primarily in aHUS and neurological and cardiological sequelae in TTP. Prompt treatment for most cases of both conditions is with plasma exchange initially and monoclonal therapy (rituximab in TTP and eculizumab in aHUS) as the mainstay of therapy. Here we discuss the diagnosis and therapy for both disorders

Pathogenicity of anti-ADAMTS13 autoantibodies in acquired thrombotic thrombocytopenic purpura.

BACKGROUND: Acquired thrombotic thrombocytopenic purpura (TTP) is an autoimmune disease in which anti-ADAMTS13 autoantibodies cause severe enzyme deficiency. ADAMTS13 deficiency causes the loss of regulation of von Willebrand factor multimeric size and platelet-tethering function, which results in the formation of disseminated microvascular platelet microthrombi. Precisely how anti-ADAMTS13 autoantibodies, or antibody subsets, cause ADAMTS13 deficiency (ADAMTS13 activity generally < 10%) has not been formally investigated. METHODS: We analysed 92 acquired TTP episodes at presentation, through treatment and remission/relapse using epitope mapping and functional analyses to understand the pathogenic mechanisms of anti-ADAMTS13 IgG. RESULTS: 89/92 of TTP episodes had IgG recognising the ADAMTS13 N-terminal domains. The central spacer domain was the only N-terminal antigenic target detected. 38/92 TTP episodes had autoantibodies recognising the N-terminal domains alone; 54/92 TTP episodes also had antibodies against the ADAMTS13 C-terminal domains (TSP2-8 and/or CUB domains). Changes in autoantibody specificity were detected in 9/16 patients at relapse, suggesting a continued development of the disease. Functional analyses on IgG from 43 patients revealed inhibitory IgG were limited to anti-spacer domain antibodies. However, 15/43 patients had autoantibodies with no detectable inhibitory action and as many as 32/43 patients had autoantibodies with inhibitory function that was insufficient to account for the severe deficiency state, suggesting that in many patients there is an alternative pathogenic mechanism. We therefore analysed plasma ADAMTS13 antigen levels in 91 acquired TTP presentation samples. We demonstrated markedly reduced ADAMTS13 antigen levels in all presentation samples, median 6% normal (range 0-47%), with 84/91 patients having < 25% ADAMTS13 antigen. ADAMTS13 antigen in the lowest quartile at first presentation was associated with increased mortality (odds ratio 5.7). CONCLUSIONS: Anti-spacer domain autoantibodies are the major inhibitory antibodies in acquired TTP. However, depletion of ADAMTS13 antigen (rather than enzyme inhibition) is a dominant pathogenic mechanism. ADAMTS13 antigen levels at presentation have prognostic significance. Taken together, our results provide new insights into the pathophysiology of acquired TTP

Cosolver2B: An Efficient Local Search Heuristic for the Travelling Thief Problem

Real-world problems are very difficult to optimize. However, many researchers have been solving benchmark problems that have been extensively investigated for the last decades even if they have very few direct applications. The Traveling Thief Problem (TTP) is a NP-hard optimization problem that aims to provide a more realistic model. TTP targets particularly routing problem under packing/loading constraints which can be found in supply chain management and transportation. In this paper, TTP is presented and formulated mathematically. A combined local search algorithm is proposed and compared with Random Local Search (RLS) and Evolutionary Algorithm (EA). The obtained results are quite promising since new better solutions were found.Comment: 12th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA) 2015. November 17-20, 201