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Showing 1 to 20 of 41 for “"Knapsack problem"”.
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A complementary heuristic for the unbounded knapsack problem
As a solution algorithm for Unbounded Knapsack Problem, the performance analysis of density-ordered greedy heuristic, weight-ordered greedy heuristic, value-ordered greedy heuristic, extended greedy heuristic and total-value heuristic has been done. Empirical experiments on different test problems …
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Public key cryptography and the zero-one knapsack problem
… the Merkle-Hellman system based on the zero-one knapsack problem is presented. Standard attacks on the zero-one knapsack problem are rejected as too time-consuming. Herlestam's proposed attack is discussed in detail. The results of theoretical examination and computer tests show that it is not …
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A multiscale approximation algorithm for the cardinality constrained knapsack problem
… algorithm for the cardinality constrained knapsack problem. The algorithm consists of three steps: a rounding and reduction step where a hierarchical representation of the problem data ranging from coarse to fine is generated, a solution step where a coarse solution is computed, and a …
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A Stochastic Approach to Modeling Aviation Security Problems Using the KNAPSACK Problem
… a system response function is introduced and the problem of determining the optimal system response function that minimizes the false alarm rate, while meeting the false clear standard, is formulated as a decision problem and proven to be NP-complete. Two heuristic procedures, the Greedy algorithm …
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Robust optimization of linear optimization problems and an approximation approach to solve robust Knapsack Problem
… of items whose total weight does not exceed the knapsack capacity, and whose profit is a maximum. In the robust KP the goal is to find a subset of items whose total weight does not exceed the knapsack capacity, and remains near maximum for the worst scenario. Solving the robust KP exactly is …
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Faster fully polynomial approximation schemes for Knapsack problems
… returns ... -optimal solution to a maximization problem of size n, which runs in polynomial time in both ... We develop faster FPTASs for several classes of knapsack problems. In this thesis, we will first survey the relevant literature in FPTASs for knapsack problems. We propose the use of …
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An Integrated Real-Time and Security Scheduling Framework for CPS
… execution times of tasks. Then, we transform the problem of maximizing security, subject to schedulability, into a variant of the knapsack problem. To make this approach more practical, we implement a fully polynomial time approximation scheme (FPTAS) that reduces the time complexity of solving …
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A Model for the Design of Distributed Databases (Concurrency Control, Update Synchronization, File Allocation)
… developing a model to solve the File Allocation Problem (FAP). The model integrates two major design issues namely Concurrency Control and Data Distribution. The central node locking mechanism is incorporated in developing a non linear integer programming model. Two solution algorithms are …
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Two essays in behavioral operations management
PAPER 1 (knapsack problem): Selecting the most valuable projects given a finite budget constraint is a recurring decision challenge in all organizations. The optimization literature has long recognized the mathematical complexities of this knapsack problem. However, these complexities along with …
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Decentralized control for UAV path planning and task allocation
… approach was first developed that treats the problem as a Multi-dimensional, Multiple-Choice Knapsack Problem. Paths are selected and task assigned while minimizing the UAV team's overall mission cost. Next, a SIMULINK-based centralized simulation environment was created. This simulation uses …
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Minimizing Total Delivered Cost of Stamped Assemblies Through Sourcing Optimization
… integer programming framework derived from the knapsack problem, the model evaluates all production scenarios to minimize total costs while adhering to capacity and capability constraints. Results demonstrate the model's effectiveness in identifying cost-saving and alternate sourcing strategies. …
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Globally optimal algorithms for multiple-transform signal compression
… programming and related to the multiple-choice knapsack problem. These algorithms are then compared to two other previous algorithms. We analyze the energy compaction performance of these algorithms in terms of different block-sizes and different input characteristics. We then extend all of …
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Efficient Optimal and Approximate Algorithms in Optimization Under Uncertainty
… What orders should we accept?). These problems can be solved naively by reformulating the problem as a deterministic problem, but this can dramatically increase the size of the problem making the naive reformulation to be computationally expensive to solve. We aim to develop efficient …
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An Efficient Knapsack-Based Approach for Calculating the Worst-Case Demand of AVR Tasks
… demand of AVR tasks by transforming the problem into a variant of the knapsack problem. We then propose a framework to systematically narrow down the search space associated with finding the worst-case demand of AVR tasks. Experimental results show that our approach is at least 10 times …
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Parametric approaches to fractional programs: Analytical and empirical study
<p>Fractional programming is used to model problems where the objective function is a ratio of functions. A parametric modeling approach provides effective technique for obtaining optimal solutions of these fractional programming problems. Although many heuristic algorithms have been proposed and …
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Generating cutting planes through inequality merging on multiple variables in knapsack problems
… A commonly studied integer program is the knapsack problem, which has applications including project and portfolio selection, production planning, inventory problems, profit maximization applications and machine scheduling. Integer programs are computationally difficult and currently …
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A Multi-Agent Design for Power Distribution Systems Automation
… and restoration. FA can solve the restoration problem using the existing algorithms for the 0-1 Knapsack problem.;A novel Q-learning mechanism is also introduced to support the FAs in decision making for restoration. Also a distributed MAS-Based Load Shedding (LS) technique has been used to …
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DF-DTM :explorando redundância de tarefas em dataflow
… follows a MapReduce (MR) model and the unbounded knapsack problem (KS). Our results shows a remarkable potential redundancy rate of approximate 98.83%, 54.73%, 72.35%, 99.73% for the benchmarks applications LCS, MR, 3-DES and GoL, respectively.
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Rejection-Free and Partial Neighbor Search MCMC Algorithms
… temperatures are widely used to solve complex problems. In order to improve its efficiency, we can also use the Rejection-Free version of the Metropolis algorithm, which avoids the inefficiency of rejections by considering all the neighbors at every step. In addition, in optimization questions, …
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New frontiers in population-based multi-objective feature selection
… selection, along with binary optimization problems in general, is a NP-hard problem since the size of search space increases exponentially by the increase of the number of features, so especially in high-dimensional spaces, it can be very challenging. We propose three innovative approaches …
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