Search Results - genetic algorithm-constraint programming

A Novel GA-CP Method for Fixed-Type Multi-Robot Collaborative Scheduling in Flexible Job Shop by Huang, Jin, Li, Xinyu, Gao, Liang

“…With the rapid development of intelligent manufacturing, multi-robot collaborative systems are increasingly integrated into various production processes. In…”
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A constraint programming-based genetic algorithm for capacity output optimization by Chin, Jeng Feng, Tan, Melissa Chea-Ling

“…Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company…”
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Resource portfolio planning of make-to-stock products using a constraint programming-based genetic algorithm by Wang, S.M., Chen, J.C., Wang, K.-J.

“…The investment on facilities for manufacturing high-tech products requires a large amount of capital. Even though the demands of such products change…”
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Hybrid Flow-Shop: a Memetic Algorithm Using Constraint-Based Scheduling for Efficient Search by Jouglet, Antoine, Oğuz, Ceyda, Sevaux, Marc

“… (genetic algorithm, constraint programming based branch-and-bound algorithm, and memetic algorithm…”
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A constraint programming-based genetic algorithm (CPGA) for capacity output optimization by Goh, Kate Ean Nee, Chin, Jeng Feng, Loh, Wei Ping, Tan, Melissa Chea-Ling

“…Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company…”
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The dual-resource-constrained re-entrant flexible flow shop a constraint programming approach and a hybrid genetic algorithm by Mlekusch, Johanna, Hartl, Richard F.

“…: a constraint programming model and a hybrid genetic algorithm with a single-level solution representation and an efficient decoding heuristic…”
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Adopting co-evolution and constraint-satisfaction concept on genetic algorithms to solve supply chain network design problems by Chang, Ying-Hua

“… In the past, mathematical programming and a general heuristics algorithm were used to solve globalized supply chain network design problems…”
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A constraint programming approach and a hybrid of genetic and K-means algorithms to solve the p-hub location-allocation problems by Rabbani, Masoud, Mokhtarzadeh, Mahdi, Manavizadeh, Neda

“… Hubs act as switching points to reduce the transportation cost. In this study, two new solution methods, a constraint programming (CP…”
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Design and Optimization of Three-Phase Dual-Active-Bridge Converters for Electric Vehicle Charging Stations by Nguyen, Duy-Dinh, Bui, Ngoc-Tam, Yukita, Kazuto

“… Switching frequency, peak flux density, number of turns, number of layers, etc., were optimized using non-linear programming technique for minimizing the overall converter loss…”
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Combining constraint programming and genetic algorithm for dynamic scheduling problems by Elkhyari, Abdallah, Bellabdaoui, Adil

“…This paper introduces a new method based on constraint programming (CP) and genetic algorithm (GA…”
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Stochastic simulation-based genetic algorithm for chance constraint programming problems with continuous random variables by Jana, R. K., Biswal, M. P.

“…In this article, we present a stochastic simulation-based genetic algorithm for solving chance constraint programming problems, where the random variables involved in the parameters follow any continuous distribution…”
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A hybrid algorithm coupling genetic programming and Nelder–Mead for topology and size optimization of trusses with static and dynamic constraints by Assimi, Hirad, Jamali, Ali

“…•Genetic programming used for truss optimization with static and dynamic constraints…”
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Stochastic simulation based genetic algorithm for chance constraint programming problems with some discrete random variables by Jana, R. K., Biswal, M. P.

“…A stochastic simulation based genetic algorithm (GA) is presented, in this paper, for solving chance constraint programming problems in which the random variables follow some discrete distributions…”
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CONSTRAINT PROGRAMMING AND GENETIC ALGORITHM by Kotecha, Prakash R., Bhushan, Mani, Gudi, Ravindra D.

“…The following sections are included: Introduction Constraint Programming Working principle Example Features of CP Determination of multiple optimal solutions Determination of pareto fronts along with multiple realizations Comparison…”
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Genetic Algorithm Combination of Boolean Constraint Programming for Solving Course of Action Optimization in Influence Nets by Zhu, Yanguang, Qin, Dongliang, Zhu, Yifan, Cao, Xingping

“… A novel method of Genetic Algorithm (GA) combination of Boolean Constraint…”
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Divisible load scheduling in distributed system with buffer constraints: genetic algorithm and linear programming approach by Suresh, S., Mani, V., Omkar, S. N., Kim, H. J.

“…Scheduling divisible loads in a single-level tree network/system with processors having finite buffer size is addressed. In earlier studies in divisible load…”
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Scheduling Scientific Workflow Applications with Deadline and Budget Constraints Using Genetic Algorithms by Yu, Jia, Buyya, Rajkumar

“… Scheduling such interdependent tasks on utility Grid environments need to consider users′ QoS requirements. In this paper, we present a genetic algorithm approach…”
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Constraint Programming and Genetic Algorithm Prakash R. Kotecha, Mani Bhushan and Ravindra D. Gudi

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Optimization of capacitated vehicle routing problem with alternative delivery, pick-up and time windows: A modified hybrid approach by Sitek, Paweł, Wikarek, Jarosław, Rutczyńska-Wdowiak, Katarzyna, Bocewicz, Grzegorz, Banaszak, Zbigniew

“…In this paper, the optimization of Capacitated Vehicle Routing Problem with Alternative Delivery, Pick-up and Time windows is considered. The development of…”
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Extension of a hybrid Genetic Algorithm for nonlinear programming problems with equality and inequality constraints by Fung, Richard Y.K., Tang, Jiafu, Wang, Dingwei

“…As an extension of the hybrid Genetic Algorithm-HGA proposed by Tang et al. (Comput. Math. Appl. 36 (1998) 11), this paper focuses on the critical techniques in the application of the GA to nonlinear programming…”
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