The problem of protein sequence alignment is the main starting point for biological analysis of genomic information. A new approach to global pairwise sequence alignment is proposed. This approach is formulated in a m...
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The problem of protein sequence alignment is the main starting point for biological analysis of genomic information. A new approach to global pairwise sequence alignment is proposed. This approach is formulated in a mathematically rigorous way, as a mixedintegerlinearoptimization (MILP) problem. Not only does the proposed formulation guarantee the identification of the global optimal alignment, but it also allows for a complete rank-ordered list of any number of user specified top ranking pairwise alignments and for the incorporation of restraints based on restrictions necessary to maintain biological function. This approach has been applied to the alignment of transmembrane helices and serine proteases to demonstrate its utility and advantages over other algorithms.
A global supply network planning model for application in the production of chemical commodities is presented. Major modules of the model formulation reflect sales, distribution, production, and procurement activities...
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ISBN:
(纸本)9781424415281
A global supply network planning model for application in the production of chemical commodities is presented. Major modules of the model formulation reflect sales, distribution, production, and procurement activities. The objective of the model is to maximize profit by coordinating all activities within the supply chain. The model formulation is related to a real industry case.
The problem of protein sequence alignment is the main starting point for biological analysis of genomic information. A new approach to global pairwise sequence alignment is proposed. This approach is formulated in a m...
详细信息
The problem of protein sequence alignment is the main starting point for biological analysis of genomic information. A new approach to global pairwise sequence alignment is proposed. This approach is formulated in a mathematically rigorous way, as a mixedintegerlinearoptimization (MILP) problem. Not only does the proposed formulation guarantee the identification of the global optimal alignment, but it also allows for a complete rank-ordered list of any number of user specified top ranking pairwise alignments and for the incorporation of restraints based on restrictions necessary to maintain biological function. This approach has been applied to the alignment of transmembrane helices and serine proteases to demonstrate its utility and advantages over other algorithms.
Job-shop scheduling has been subject to investigations in the field of operations research and business informatics for many years. Traditional optimization techniques, like linear programming and branching-and-boundi...
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Job-shop scheduling has been subject to investigations in the field of operations research and business informatics for many years. Traditional optimization techniques, like linear programming and branching-and-bounding are usually not applicable are to real-world scheduling because the underlying problem is NP-hard. Recently, heuristic techniques like simulated annealing and genetic. algorithms have been proposed to solve scheduling problems. These techniques do not guarantee optimal solutions, but they compute good solutions in acceptable time. In this paper, application of simulated annealing and genetic algorithms to scheduling are investigated with respect to solution quality and computing time. Optimal solutions required for the comparisons were determined by mixed-integer linear optimization.
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