Bin packing problem with conflicts(BPPC) is a complex combinatorialoptimization problem originated from logistics, whose objective is packing all the items withthe least number of bins and satisfying the conflict co...
详细信息
Bin packing problem with conflicts(BPPC) is a complex combinatorialoptimization problem originated from logistics, whose objective is packing all the items withthe least number of bins and satisfying the conflict constraints among the items. In this paper, we firstly give the description and 0-1 integerprogramming model of BPPC, and then transform the model into the representation of conflict graph structure. After that, an ant colony optimization(ACO) algorithm framework is proposed for solving the conflict elimination procedure of BPPC based on a graph coloring heuristic, according to the results of conflict elimination, an improved first-fit decreasing algorithm is used to finish the packing operations of the subsets of items without conflicts. the experiments show that the improve ACO algorithm in this paper is valid and could provide a feasible and high-quality solutions of BPPC efficiently.
this article examines the management of user traffic to the network access point and within the network, from the user's access point to the destination server containing the required information. this study is co...
详细信息
Nowadays, we're all familiar withthe speed of e-commerce development, but we have to admit that logistics industry in rural areas is still in its infancy. As deficient rural logistics network has restricted the r...
详细信息
ISBN:
(纸本)9781509061204
Nowadays, we're all familiar withthe speed of e-commerce development, but we have to admit that logistics industry in rural areas is still in its infancy. As deficient rural logistics network has restricted the rural development to a certain extent, this research field becomes a hot topic. However, most existing papers on forward and reverse logistics network design were primarily concerned with minimizing the total cost, neglecting the time sensitivity. In this paper, we propose a rural forward and reverse logistics network mode of e-commerce platform and a multiobjective mixed-integer linear programming model for logistics network design. To solve the NP-hard problem of the model, the nondominated sorting genetic algorithm II (NSGA-II) has been used. At last, the model has been used to design forward and reverse rural logistics network in Pinggu district of Beijing as an example, and the result show that the model is efficient for establishing virtuous rural logistics network.
this chapter presents two global optimization approaches for identifying the most critical combination of vulnerable links in a transportation network. the first approach is formulated with a bi-level framework. It ca...
详细信息
A dynamic scheduling for the constrained resource with partially substitutability based on the critical chain can not only improve the work efficiency of the system, but also achieve the replacement of resources and r...
详细信息
In the last years, traffic over wireless networks has been increasing exponentially, due to the impact of Internet of things (IoT) and Smart Cities. Current networks must adapt to and cope withthe specific requiremen...
详细信息
In the last years, traffic over wireless networks has been increasing exponentially, due to the impact of Internet of things (IoT) and Smart Cities. Current networks must adapt to and cope withthe specific requirements of IoT applications since resources can be requested on-demand simultaneously by multiple devices on different locations. One of these requirements is low latency, since even a small delay for an IoT application such as health monitoring or emergency service can drastically impact their performance. To deal withthis limitation, the Fog computing paradigm has been introduced, placing cloud resources on the edges of the network to decrease the latency. However, deciding which edge cloud location and which physical hardware will be used to allocate a specific resource related to an IoT application is not an easy task. therefore, in this paper, an integer Linear programming (ILP) formulation for the IoT application service placement problem is proposed, which considers multiple optimization objectives such as low latency and energy efficiency. Solutions for the resource provisioning of IoT applications within the scope of Antwerp's City of things testbed have been obtained. the result of this work can serve as a benchmark in future research related to placement issues of IoT application services in Fog Computing environments since the model approach is generic and applies to a wide range of IoT use cases.
this paper presents two variants of Genetic Algorithms (GAs) for solving the Multiple Container Packing Problem (MCPP), which is a combinatorialoptimization problem comprising similarities to the Knapsack Problem and...
详细信息
ISBN:
(纸本)3540650784
this paper presents two variants of Genetic Algorithms (GAs) for solving the Multiple Container Packing Problem (MCPP), which is a combinatorialoptimization problem comprising similarities to the Knapsack Problem and the Bin Packing Problem. Two different representation schemes are suggested, namely direct encoding and order based encoding. While order based encoded solutions are always feasible, a repair algorithm is used in case of direct encoding to ensure feasibility. Additionally, local improvement operators have been applied to both GA variants. the proposed algorithms were empirically compared by using various sets of differently sized test data. Order based encoding performed better for problems with fewer items, whereas direct encoding exhibited advantages when dealing with larger problems. the local improvement operators lead in many cases not only to better final results but also to shorter running times because of higher convergence rates.
Bin covering is an important optimization problem in many industrial fields, such as packaging, recycling, and food processing. the problem concerns a set of items, each with its own value, that are to be collected in...
详细信息
Bin covering is an important optimization problem in many industrial fields, such as packaging, recycling, and food processing. the problem concerns a set of items, each with its own value, that are to be collected into bins in such a way that the total value of each bin, as measured by the sum of its item values, is not lower than a target value. the optimization problem concerns maximizing the number of bins. this is a combinatorial NP-hard problem, for which true optimal solutions can only be calculated in specific cases, such as when restricted to a small number of items. To get around this problem, many suboptimal approaches exist. this paper describes a formulation of the bin covering that allows to find the true optimum for a rather large number of items, over 1000. Also presented is a suboptimal solution, which is compared to the true optimum and found to come within less than 10% of the optimum.
Traveling salesman problem (TSP) is a problem of determining the shortest path for a salesman to take to visit all cities. Although a small number of cities is easy to solve, as the number of cities increases, it’s n...
Traveling salesman problem (TSP) is a problem of determining the shortest path for a salesman to take to visit all cities. Although a small number of cities is easy to solve, as the number of cities increases, it’s not possible to solve in polynomial time as it was a combinatorial nondeterministic polynomial (NP-hard) problem. Hence, this project is implementing a genetic algorithm (GA) to solve TSP using Python programming. the focus of this paper is to analyze the GA using order crossover (OX) and random crossover (RX) and propose a combination mechanism, direct combination (OX-RX) and Dynamic Linear combination (OXRX-Linear) to optimize TSP. We test GA for OX and RX in a random set of cities, up to 75 total cities. then compare the result of the proposed combination OX-RX and OX-RXLinear. the result shows that both proposed combined mechanisms OX-RX and OX-RX-Linear improve the performance of GA in solving TSP.
In view of the current situation that different Earth Observation Satellite systems are independent in our country, which results in the failure to share resources and to cope with numerous emergency tasks effectively...
详细信息
暂无评论