Applying Gene Expression Programming for Solving One-Dimensional Bin-Packing Problems

一种用于平衡圆形装箱问题的基于虚拟力的群集算法

A Virtual-Force Based Swarm Algorithm for Balanced Circular Bin Packing Problems

针对高约束、高维的NP难平衡圆形装箱问题，提出一种基于虚拟力系统和动力学原理的群集算法，并在多达300个圆的基准上验证其有效性。

A Parallel Genetic Algorithm for Three Dimensional Bin Packing with Heterogeneous Bins

This paper presents a parallel genetic algorithm for three dimensional bin packing with heterogeneous bins using Hadoop Map-Reduce framework. The most common three dimensional bin packing problem which packs given set of boxes into minimum number of equal sized bins is proven to be NP Hard. The variation of three dimensional bin packing problem that allows heterogeneous bin sizes and rotation of boxes is computationally more harder than common three dimensional bin packing problem. The proposed Map-Reduce implementation helps to run the genetic algorithm for three dimensional bin packing with …

Evolutionary Approach for the Containers Bin-Packing Problem

This paper deals with the resolution of combinatorial optimization problems, particularly those concerning the maritime transport scheduling. We are interested in the management platforms in a river port and more specifically in container organisation operations with a view to minimizing the number of container rehandlings. Subsequently, we rmeet customers delivery deadlines and we reduce ship stoppage time In this paper, we propose a genetic algorithm to solve this problem and we present some experiments and results.

Comparing several heuristics for a packing problem

Packing problems are in general NP-hard, even for simple cases. Since now there are no highly efficient algorithms available for solving packing problems. The two-dimensional bin packing problem is about packing all given rectangular items, into a minimum size rectangular bin, without overlapping. The restriction is that the items cannot be rotated. The current paper is comparing a greedy algorithm with a hybrid genetic algorithm in order to see which technique is better for the given problem. The algorithms are tested on different sizes data.

随机键优化与线性化用于二次多约束可变尺寸装箱问题

Random-Key Optimizer and Linearization for the Quadratic Multiple Constraints Variable-Sized Bin Packing Problem

本文提出线性化模型和RKO-ACO算法，解决二次多约束可变尺寸装箱问题，改进下界计算并提升求解效果。

Evolutionary Bin Packing for Memory-Efficient Dataflow Inference Acceleration on FPGA

Convolutional neural network (CNN) dataflow inference accelerators implemented in Field Programmable Gate Arrays (FPGAs) have demonstrated increased energy efficiency and lower latency compared to CNN execution on CPUs or GPUs. However, the complex shapes of CNN parameter memories do not typically map well to FPGA on-chip memories (OCM), which results in poor OCM utilization and ultimately limits the size and types of CNNs which can be effectively accelerated on FPGAs. In this work, we present a design methodology that improves the mapping efficiency of CNN parameters to FPGA OCM. We frame the…