The traditional flexible job shop scheduling problem (FJSP) ignores transportation issues or merely introduces a time lag for transportation tasks while assuming an infinite number of transportation resources. With th...
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The traditional flexible job shop scheduling problem (FJSP) ignores transportation issues or merely introduces a time lag for transportation tasks while assuming an infinite number of transportation resources. With the development of intelligent manufacturing, automated guided vehicles (AGVs), which are the key transportation equipment for manufacturing enterprises, have been widely used for their high flexibility and stability. In addition, the increase in energy consumption and the trend of green manufacturing make it critical to take into account energy-related objectives in the decision-making of scheduling. Therefore, the multi-objective green scheduling problem of integrated flexible job shop and AGVs (MOGSP-IFJS & AGVs) is addressed in this paper. To solve this problem effectively, the multi-objective mixed-integer programming (MMIP) model is formulated to minimize total energy consumption and makespan simultaneously. An efficient heuristic algorithm (EHA) is designed to solve the MMIP model. In the EHA, one solution encoding scheme and corresponding greedy insertion decoding method considering the selection of AGVs are presented. To acquire a high-quality initial population, the population initialization method balancing the processing time and energy consumption is designed. Further, a local search strategy is presented to enhance the quality of solutions and accelerate the convergence speed of the EHA. Experiment results of 45 test instances indicate that the EHA can obtain better solutions than that of comparison algorithms, which confirms the effectiveness of the EHA for solving the MOGSP-IFJS & AGVs.
This study proposes a mathematical formulation and solution approach for a novel extension of the location-routeing problem (LRP), namely line-haul feeder LRP (LFLRP), where large vehicles (trucks) are synchronised wi...
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This study proposes a mathematical formulation and solution approach for a novel extension of the location-routeing problem (LRP), namely line-haul feeder LRP (LFLRP), where large vehicles (trucks) are synchronised with small vehicles (motorcycles) throughout delivery process. Customers are visited by site-dependent vehicles such that those not accessible by trucks must be served by motorcycles. The LFLRP is formulated as a mixed-integer linear programming model, and two efficient heuristic algorithms called EHA and Enhanced-EHA are developed to solve the problem. Experimental results show that the proposed algorithms can provide near-optimal solutions for 18 randomly generated small-scale LFLRP test instances and best-known solutions for 12 out of 19 large-scale standard LRP test instances in reasonable computation time. A cost-benefit analysis also indicates that the LFLRP model can considerably reduce total costs compared to equivalent standard LRP formulations. To provide managerial insights, a case study and sensitivity analysis of key parameters are conducted.
It is anticipated that future wireless networks will make use of more renewable energy sources, e. g., solar, wind, and hydro, etc., in order to sustain the ever-growing traffic demands, while mitigating the effects o...
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ISBN:
(纸本)9781424492688
It is anticipated that future wireless networks will make use of more renewable energy sources, e. g., solar, wind, and hydro, etc., in order to sustain the ever-growing traffic demands, while mitigating the effects of increased energy consumption. The most critical issue of developing a sustainable communications network is how to cost-effectively deploy access points (APs) with sustainable energy supplies and allocate network resources to meet the quality of service (QoS) requirements of users. In this paper, the traditional AP placement problem is revisited with sustainable power supplies. First, a constrained AP placement optimization problem is formulated. The objective is to determine the optimal placement of APs on a set of candidate locations such that the number of APs is minimized, subject to the constraints that QoS requirements of users can be fulfilled with the harvested energy. To further improve the sustainable network performance, joint power control and rate adaptation at APs is considered, based on different user demands and charging capabilities of the APs. After that, an efficient heuristic algorithm with polynomial time complexity is proposed. Extensive simulation results show that the proposed algorithm approaches the optimal solution under a variety of network settings with significantly reduced time complexity.
An efficient heuristic algorithm is proposed for the channel assignment problem in cellular mobile systems. The merit of the algorithm is the improved repetitive ordering of requirements in sequences using the determi...
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An efficient heuristic algorithm is proposed for the channel assignment problem in cellular mobile systems. The merit of the algorithm is the improved repetitive ordering of requirements in sequences using the deterministic assignment difficulties. Benchmark problems are employed to validate the performance merit of the proposed algorithm and five other well-known channel assignment schemes. The relative merit of performance is measured in terms of the number of required channels, the percentage of assignment for a fixed number of available channels and the computational time. The study shows that the proposed algorithm is superior to the other investigated algorithms. It yields the optimal assignment for most of the benchmark problems and near-optimal assignment for other cases.
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