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Titlebook: Combinatorial Optimization and Applications; 14th International C Weili Wu,Zhongnan Zhang Conference proceedings 2020 Springer Nature Switz

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Technology-Enhanced Infrastructurens, and using warehouses as starting and ending points in parcel delivery. In this paper we define the UAS Energy-constrained Delivery Scheduling problem and propose a scheduling mechanism using a multi-source A* algorithm variant. Simulation results show that our algorithm is efficient and scalable with the number of requests and network size.
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Energy-Constrained Drone Delivery Schedulingns, and using warehouses as starting and ending points in parcel delivery. In this paper we define the UAS Energy-constrained Delivery Scheduling problem and propose a scheduling mechanism using a multi-source A* algorithm variant. Simulation results show that our algorithm is efficient and scalable with the number of requests and network size.
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The Smart Grid: Anchor of the Smart City Satisfactory Partition problem is polynomial-time solvable for block graphs, (2) The Satisfactory Partition problem and its balanced version can be solved in polynomial time for graphs of bounded clicque-width, and (3) A generalized version of the Satisfactory Partition problem is W[1]-hard when parametrized by treewidth.
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The Smart Grid: Anchor of the Smart City We prove that this PSP is strongly NP-hard even when restricted to unit processing times, a common period, and 16 machines, by a reduction from the job shop scheduling problem. Finally, we propose a local search heuristic to solve the general PSP and present its experimental evaluation.
发表于 2025-3-28 00:32:40 | 显示全部楼层
The Smart Grid: Anchor of the Smart Citythe number of jobs to be scheduled and . is the length of the input’s longest precedence chain. We demonstrate that the algorithm is practical on realistic inputs, finds solutions that are close to optimal, and improves over existing algorithms on the data sets tested.
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On the Complexity of a Periodic Scheduling Problem with Precedence Relations We prove that this PSP is strongly NP-hard even when restricted to unit processing times, a common period, and 16 machines, by a reduction from the job shop scheduling problem. Finally, we propose a local search heuristic to solve the general PSP and present its experimental evaluation.
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