Monotonicity in the stock competition game with consumer search

Anupindi and Bassok investigate the impact of centralizing the stocks in a one-manufacturer-two-retailer supply chain with consumer search. They observed through numerical studies that in the decentralized scenario, the retailers’ order quantities are monotonic in the consumer search probability. This paper provides an analytical justification of this monotonicity.     

On the numerical solution of the linear complementarity problem

The well-known linear complementarity problem with definite matrices is considered. It is proposed to solve it using a global optimization algorithm in which one of the basic stages is a special local search. The proposed global search algorithm is tested using a variety of randomly generated problems; a detailed analysis of the computational experiment is given.     

Partial integration of frequency allocation within antenna positioning in GSM mobile networks

In this article we propose to partially integrate the antenna positioning (APP) and frequency allocation problems (FAP). The traditional wireless network design process examines these two major issues sequentially in order to avoid the very high complexity associated with the simultaneous resolution of the two problems. The proposed integration involves the introduction of interference protection guarantees within the APP. It is customary to define such guarantees in an intermediate step and to use them as input to FAP, in order to protect against interference in critical areas. The proposed approach consists of selecting these protections while solving the APP, allowing the optimization procedure to exploit the degrees of freedom that this would offer. Results on two real-life problem instances indicate a significant improvement in interference levels and resource utilization.     

POPMUSIC for the point feature label placement problem

Point feature label placement is the problem of placing text labels adjacent to point features on a map so as to maximize legibility. The goal is to choose positions for the labels that do not give rise to label overlaps and that minimize obscuration of features. A practical goal is to minimize the number of overlaps while considering cartographic preferences. This article proposes a new heuristic for solving the point feature label placement problem based on the application of the POPMUSIC frame. Computational experiments show that the proposed heuristic outperformed other recent metaheuristics approaches in the literature. Experiments with problem instances involving up to 10 million points show that the computational time of the proposed heuristic increases almost linearly with the problem size. New problem instances based on real data with more than 13,000 labels are proposed.     

Dynamics of spatio-temporal defects in the Taylor-Dean system

The dynamics of defects in a pattern of traveling inclined rolls has been investigated. Two regimes were identified in the neighborhood of defects: a diffusive regime, with a negative phase diffusion coefficient, and a coalescence regime in which the phase gradient diverges in time following a power law behavior. The observed periodic nucleation of defects is related to the frequency inhomogeneity induced by the disymmetry of the wave amplitude. Amplitude holes have been observed in the secondary modulated pattern. Received 23 February 1999 and Received in final form 26 May 1999     

最佳粮库地址的选择

管理部门通常要选择适当的地方建造粮库 ,所需服务范围已知 ,各部门运输量给定 .需为他们选择合适的地方 ,使总运费最少 .某乡的九个村 (A,B,C,… ,H,I)如图 1 ,各村距离给出 ,并标明它们各自上缴公粮数 .管理部门希望在村内或道路上建立一个粮库 ,最大限度地减少运输费用 .问题的解法有几种方案 ,对于本题来说 ,穷举搜索法是可行的 .另外 ,我们提出一种分析求解法 ,可找到优化解 .它利用图论的基础知识先求出图 1的各顶点间的最小路径 ,再进一步求出图的绝对中心 (即粮库的地址 ) ,其中的有关计算利用了 C++语言程序 .在此基础上 ,还可对问题的参数作更精细的分析 .概括地说 ,穷举搜索法对于简单的区域是行之有效的 .但对于更加一般化的问题 ,利用计算机可快捷准确地得到答案 .通过建立模型 ,我们得到下面两个结论 :(1 )我们找到最优解是 E点 ,其总运费为 1 2 775元 .(2 )模型具有广泛性 ,对于更一般的区域 ,可利用计算机总可以求出最优解 .     

On solving the maximum clique problem

The Maximum Clique Problem (MCP) is regarded here as the maximization of an indefinite quadratic form over the canonical simplex. For solving MCP an algorithm based upon Global Optimality Conditions (GOC) is applied. Furthermore, each step of the algorithm is analytically investigated and tested. The computational results for the proposed algorithm are compared with other Global Search approaches.     

Greatest Descent Algorithms in Unconstrained Optimization

We show that, for an unconstrained optimization problem, the long-term optimal trajectory consists of a sequence of greatest descent directions and a Newton method in the final iteration. The greatest descent direction can be computed approximately by using a Levenberg-Marquardt like formula. This implies the view that the Newton method approximates a Levenberg-Marquardt like formula at a finite distance from the minimum point, instead of the standard view that the Levenberg-Marquadt formula is a way to approximate the Newton method. With the insight gained from this analysis, we develop a two-dimensional version of a Levenberg-Marquardt like formula. We make use of the two numerically largest components of the gradient vector to define here new search directions. In this way, we avoid the need of inverting a high-dimensional matrix. This reduces also the storage requirements for the full Hessian matrix in problems with a large number of variables. The author thanks Mark Wu, Professors Sanyang Liu, Junmin Li, Shuisheng Zhou and Feng Ye for support and help in this research as well as the referees for helpful comments.     

A neighborhood search heuristic for pre-marshalling export containers

In a yard where export containers are piled up, only those on the top are directly accessible to the stacking equipment. As a result, extra rehandles may occur when lifting them up for loading onto ships. One way to improve operational efficiency is to pre-marshal the containers in such an order that it fits the loading sequence. This paper proposes a model to develop a movement plan to improve the layout of containers in a bay. The proposed heuristic consists of a neighborhood search process, an integer programming model, and three minor subroutines. Each of the components plays a different role in the heuristic. Several sets of testing results demonstrate the performance of the heuristic as well as the contributions of the components.     

Project Scheduling with Multiple Modes: A Genetic Algorithm

In this paper we consider the resource-constrained project scheduling problem with multiple execution modes for each activity and makespan minimization as objective. We present a new genetic algorithm approach to solve this problem. The genetic encoding is based on a precedence feasible list of activities and a mode assignment. After defining the related crossover, mutation, and selection operators, we describe a local search extension which is employed to improve the schedules found by the basic genetic algorithm. Finally, we present the results of our thorough computational study. We determine the best among several different variants of our genetic algorithm and compare it to four other heuristics that have recently been proposed in the literature. The results that have been obtained using a standard set of instances show that the new genetic algorithm outperforms the other heuristic procedures with regard to a lower average deviation from the optimal makespan.