Open AccessBook
Discrete Optimization
R. Gray Parker,Ronald L. Rardin +1 more
Reads0
Chats0
About:
The article was published on 1988-09-11 and is currently open access. It has received 48 citations till now. The article focuses on the topics: Continuous optimization & Discrete optimization.read more
Citations
More filters
Journal ArticleDOI
An LP-based algorithm for the data association problem in multitarget tracking
TL;DR: This work presents a linear programming (LP) based approach for solving the data association problem (DAP) in multiple target tracking using an iterated K-scan sliding window technique and presents a compact formulation of the DAP.
Journal ArticleDOI
A time-varying transfer function for balancing the exploration and exploitation ability of a binary PSO
TL;DR: The experimental results demonstrate that TVT-BPSO outperforms existing BPSO variants on both low-dimensional and high-dimensional classical knapsack problems, as well as a 200-member truss problem, suggesting that the new transfer function is able to better scale to high dimensional combinatorial problems than the existing B PSO variants and other metaheuristic algorithms.
Dissertation
Modeling transportation problems using concepts of swarm intelligence and soft computing
Panta Lučić,Dušan Teodorović +1 more
TL;DR: This research is partially devoted to the development of a new system based on foraging behavior of bee colonies - Bee System, which was tested through many instances of the Traveling Salesman Problem and Schedule Synchronization in Public Transit.
Dissertation
Physical database design decision algorithms and concurrent reorganization for parallel database systems
TL;DR: The studies indicate that a low priority for the reorganization process compared to the priorities for the workload processes is often but not always best and a method to estimate the costs of executing a reorganization with a workload is developed, and some decision algorithms are developed.
Journal ArticleDOI
Exploiting process plan flexibility in production scheduling : A multi-objective approach
TL;DR: The aim of machine loading is to generate a set of efficient (non-dominated) solutions with respect to the load balancing and cost objectives, leaving to the user the task of selecting a compromise solution.
References
More filters
Journal ArticleDOI
An LP-based algorithm for the data association problem in multitarget tracking
TL;DR: This work presents a linear programming (LP) based approach for solving the data association problem (DAP) in multiple target tracking using an iterated K-scan sliding window technique and presents a compact formulation of the DAP.
Journal ArticleDOI
A time-varying transfer function for balancing the exploration and exploitation ability of a binary PSO
TL;DR: The experimental results demonstrate that TVT-BPSO outperforms existing BPSO variants on both low-dimensional and high-dimensional classical knapsack problems, as well as a 200-member truss problem, suggesting that the new transfer function is able to better scale to high dimensional combinatorial problems than the existing B PSO variants and other metaheuristic algorithms.
Dissertation
Modeling transportation problems using concepts of swarm intelligence and soft computing
Panta Lučić,Dušan Teodorović +1 more
TL;DR: This research is partially devoted to the development of a new system based on foraging behavior of bee colonies - Bee System, which was tested through many instances of the Traveling Salesman Problem and Schedule Synchronization in Public Transit.
Dissertation
Physical database design decision algorithms and concurrent reorganization for parallel database systems
TL;DR: The studies indicate that a low priority for the reorganization process compared to the priorities for the workload processes is often but not always best and a method to estimate the costs of executing a reorganization with a workload is developed, and some decision algorithms are developed.
Journal ArticleDOI
Exploiting process plan flexibility in production scheduling : A multi-objective approach
TL;DR: The aim of machine loading is to generate a set of efficient (non-dominated) solutions with respect to the load balancing and cost objectives, leaving to the user the task of selecting a compromise solution.