{"responseHeader":{"status":0,"QTime":3,"params":{"q":"{!q.op=AND}id:\"99683\"","hl":"true","hl.simple.post":"","hl.fragsize":"5000","fq":"!embargo_tdt:[NOW TO *]","hl.fl":"ocr_t","hl.method":"unified","wt":"json","hl.simple.pre":""}},"response":{"numFound":1,"start":0,"docs":[{"file_name_t":"Gu-Parallel_Algorithms.pdf","thumb_s":"/64/b7/64b71e732f410f6453241a7edb74e1d2451cc2be.jpg","oldid_t":"compsci 7796","setname_s":"ir_computersa","restricted_i":0,"format_t":"application/pdf","modified_tdt":"2016-05-25T00:00:00Z","file_s":"/18/88/18889b7e88223eef829faa3c2331cdf54f0be20c.pdf","title_t":"Page 35","ocr_t":"17 a,rnple, Stone and Sipala [181] presented two different generic models of probabilistic behavior of a depth-first search to find the first solution. Stone and Stone [182]6 continued to explore the average cost of the search complexity for the first solution for a popular testbed, i.e., an n-queens problem. Freuder discussed the problem structure and the search order and provided heuristic guidance in selecting a vertiĀcal (variable) ordering in a CLP problem to find one solution (46] . Recently, based on the sparseness in the constraint network and the simplicity of tree-structured CLP, Dechter and Pearl gave a general approach that is able to generate heuristic advice to guide the horizontal (value) ordering selection strategies for a CLP search, also for one solution case [31]. Moreover, Nicol [136] confirmed Stone and Sipala's model and discussed the backtracking search for m solutions. 1.2.2 Complexity of the AC Algorithms Figure 1.4 shows some AC algorithms with the worst case time complexity on the top. Montanari [129] formulated the networks of constraints which motivated much subsequent work toward finding efficient consistency algorithms. More vari-ations are emerging for algorithms based on consistency, particularly on arc con-sistency. ~1ackworth [115] first discussed existing algorithms in diverse problem areas and consolidated a family of consistency algorithms. He gave three sequen-tial arc consistency algorithms AC-1, AC-2 (i.e., H-'altz filtering [202]), and AC-3. The time complexities7 for these algorithms are O(n3m3 ), O(n3m2 ) and O(n3m2 ) , respectively. Mohr and Henderson [128] further showed an optimal, sequential arc consistency algorithm AC-4, which is of O(n2m2 ) time complexity. Mackworth et 6 Most of the results in this paper relate to search for one solution . 7Note that the time complexity for an algorithm is defined as the number of operations taken to complete the computation specified in the algorithm in terms of input size. Often , it usually takes large numbers of machine instructions (and/or clock cycles) to run each operation of the algorithm on an existing general-purpose computer machine .","id":99683,"created_tdt":"2016-05-25T00:00:00Z","parent_i":99969,"_version_":1679953745514856448}]},"highlighting":{"99683":{"ocr_t":[]}}}