A coevolutionary algorithm for the flexible delivery and pickup problem with time windows

This paper addresses a flexible delivery and pickup problem with time windows (FDPPTW) and formulates the problem into a mixed binary integer programming model in order to minimize the number of vehicles and to minimize the total traveling distance. This problem is shown to be NP-hard. In this study, therefore, a coevolutionary algorithm incorporated with a variant of the cheapest insertion method is developed to speed up the solution procedure. The FDPPTW scheme overcomes the shortcomings of the existing schemes for the delivery and pickup problems. By testing with some revised Solomon's benchmark problems, the computational results have shown the efficiency and the effectiveness of the developed algorithm.     

A memetic algorithm for a multistage capacitated lot-sizing problem

We present a heuristic approach to solve a complex problem in production planning, the multistage lot-sizing problem with capacity constraints. It consists of determining the quantity to be produced in different periods in a planning horizon, such that an initially given demand forecast can be attained. We consider setup costs and setup times. Due the complexity to solve this problem, we developed methods based on evolutionary metaheuristics, more specifically a memetic algorithm. The proposed heuristics are evaluated using randomly generated instances and well-known examples in the literature.     

基于自适应遗传算法的一类非线性规划问题的新算法

传统的方法解答非线性规划问题存在着有进入局部最优、效率低、甚至根本得不出结果的局限性,而遗传算法中用不变的p_c和p_m来控制进化,很容易导致早熟,降低算法搜索效率。根据适应度自动对交叉概率p_c和变异概率p_m进行调整,提出一种新的遗传算法。通过对6个测试函数的仿真实验,结果表明本算法是非常有效的。     

A heuristic algorithm for a multi-product dynamic lot-sizing and shipping problem

This paper analyzes a dynamic lot-sizing problem, in which the order size of multiple products and a single container type are simultaneously considered. In the problem, each order (product) placed in a period is immediately shipped by some containers in the period and the total freight cost is proportional to the number of containers used. It is also assumed that backlogging is not allowed. The objective of this study is to simultaneously determine the lot-sizes and the transportation policy that minimizes the total costs, which consist of production cost, inventory holding cost, and freight cost. Because this problem is NP-hard, a heuristic algorithm with an adjustment mechanism is proposed based on the optimal solution properties. The computational results from a set of simulation experiment are also presented.     

Economic lot and delivery scheduling problem for multi-stage supply chains

The economic lot and delivery scheduling problem for a multi-stage supply chain comprising multiple items is studied in this paper. It is required to develop a synchronized replenishment strategy, and specify the sequence of production and the replenishment cycle time that achieves synchronization through the supply chain at minimum cost. The problem is presented in a novel formulation based on the quadratic assignment representation. The common cycle time and the integer multipliers policies are adopted to accomplish the desired synchronization. The two policies are represented by nonlinear models handled through a hybrid algorithm. The algorithm combines linearization, outer approximation and Benders decomposition techniques. Results of the two policies demonstrate that a cost reduction up to16.3% can be attained by employing the integer multipliers policy instead of the common cycle time. Computational experiments show the efficiency of the new formulation and solution algorithm by reaching the optimal solution for large problem instances in short time.     

A tabu search algorithm for the relocation problem in a warehousing system

Relocation of items in a warehousing system is usually used when the handling machines become the bottleneck. This paper addresses the optimization problem of relocation in a warehouse with dynamic operating policy. An integer linear programming formulation is proposed. A two-stage heuristic method is developed to generate an initial solution. A tabu search algorithm is proposed to improve the solution. Two relocation policies are studied and their performances are compared.     

试论国际竞争力的理论概念与分析方法

所谓国际竞争力，有产品竞争力，企业竞争力，产业竞争力以及国家竞争力之分。从经济学视角看，关于各类竞争力的讨论分别对应着微观，中观和宏观层次。对各类竞争力主体内容的深入剖析更为清楚地表明，由于所分析的竞争力种类不同以及分析目的不同，对竞争力的分析范式也就相应不同。在产业竞争优势理论框架下设立的经济分析范式既可以用于分析以国家为主体的产品国家竞争力，在一定意义上也可以用于分析企业国际竞争力。价值链的分析方法则提供了评价一国某一产业中某种生产经营活动具有何种国际竞争力的思路。各种显示性能指标和分析性指标可以用来测度产品和产业国际竞争力，以及说明相对竞争优势和绝对竞争优势。     

A novel differential evolution algorithm for joint replenishment problem under interdependence and its application

In this paper, we propose a new differential evolution (DE) algorithm for joint replenishment of inventory using both direct grouping and indirect grouping which allows for the interdependence of minor ordering costs. Since solutions to the joint replenishment problem (JRP) can be represented by integer decision variables, this makes the JRP a good candidate for the DE algorithm. The results of testing randomly generated problems in contrastive numerical examples and two extended experiments show that the DE algorithm provides close to optimal results for some problems than the evolutionary algorithm (EA), which has been proved to be an efficient algorithm. Moreover, the DE algorithm is faster than the EA for most problems. We also conducted a case study and application results suggest that the proposed model is successful in decreasing total costs of maintenance materials inventories significantly in two power companies.     

A block mining and re-combination enhanced genetic algorithm for the permutation flowshop scheduling problem

The goal of block mining is to obtain a set of genes that contain dependency among gene relationships. Such blocks without overlapping of genes can be further merged to form a new chromosome and the quality of the new chromosome can be greatly improved. Based on this concept, we propose a novel block mining method that is able to locate common structures or to establish new blocks (like a small piece of puzzle) from a set of high fit chromosomes. The identified blocks (puzzles) will also be updated generation by generation through the newly updated high fit chromosomes. We develop a heuristic re-combination procedure to form a new chromosome by re-combining the blocks. We call the new chromosomes generated as artificial chromosomes (ACs) and inject them into the evolutionary process when the convergence slope of the evolutionary process is less than a predefined threshold. This new algorithm retains the regular simple genetic algorithm (SGA) operations of crossover and mutation, and utilizes the ACs generated from elites to speed up the convergence process. Experimental results indicate that the puzzle-based method of chromosome generation is very efficient and effective in solving the traditional permutation flowshop scheduling problem. The new method can be applied to tackle other NP-complete problems such as scheduling and vehicle routing problems.     

The systemic approach to technological education: effects of transferred learning in resolving a physics problem

The purpose of this study is to verify whether pupils (15–16 years old) who have received technology education on a systemic approach of industrial systems, are better than other pupils (of the same age but from other academic domains such as literary ones or ones that are economics-based) at solving physical science problems which involve systemic reasoning. The results show that there is a positive transfer effect of the systems approach applied to industrial automatisms on systems of another nature (hydrodynamic and electrical problems). However, this effect is less important for the pupils who study engineering sciences initiation for just 1?year (ISI) than for those who continue this education (SI) for a further year.     

The Technology Fair: a project-based learning approach for enhancing problem solving skills and interest in design and technology education

This paper presents an innovative way in which university education can help pre-service teachers become better problem-solvers. The central idea is to use the “Technology Fair” as a means for promoting pre-service teachers pedagogical content knowledge about technological problem solving skills. This innovation is supported with results from a study carried out in autumn 2004. The purpose of the study was to investigate the influence of a procedure of working with primary school children to complete and present a technology fair project, on the educational value and meanings attached to problem solving skills by pre-service teachers. Pre-tests, mid-test and post-tests were administered to the pre-service teachers before, during, and after the preparation of the technology fair, respectively. A number of pre-service teachers were selected and interviewed after the completion of the technology fair. Data were also collected from reflective diaries kept by the pre-service teachers during the preparation phase of the technology fair. Analysis of the results indicates that the technology fair contributes to the development of positive values and attitudes in technology education and has a significant influence on improving pre-service teachers understanding and application of problem solving strategies within the domain of technology.     

A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times,sequence-dependent setup times and learning effect

This paper addresses multi-objective (MO) optimization of a single-model assembly line balancing problem (ALBP) where the operation times of tasks are unknown variables and the only known information is the lower and upper bounds for operation time of each task. Three objectives are simultaneously considered as follows: (1) minimizing the cycle time, (2) minimizing the total equipment cost, and (3) minimizing the smoothness index. In order to reflect the real industrial settings adequately, it is assumed that the task time is dependent on worker(s) (or machine(s)) learning for the same or similar activity and sequence-dependent setup time exists between tasks. Finding an optimal solution for this complicated problem especially for large-sized problems in reasonable computational time is cumbersome. Therefore, we propose a new solution method based on the combination of particle swarm optimization (PSO) algorithm with variable neighborhood search (VNS) to solve the problem. The performance of the proposed hybrid algorithm is examined over several test problems in terms of solution quality and running time. Comparison with an existing multi-objective evolutionary computation method in the literature shows the superior efficiency of our proposed PSO/VNS algorithm.     

The growing complexity of content delivery networks: Challenges and implications for the Internet ecosystem

Since the commercialization of the Internet, content and related applications, including video streaming, news, advertisements, and social interaction have moved online. It is broadly recognized that the rise of all of these different types of content (static and dynamic, and increasingly multimedia) has been one of the main forces behind the phenomenal growth of the Internet, and its emergence as essential infrastructure for how individuals across the globe gain access to the content sources they want. To accelerate the delivery of diverse content in the Internet and to provide commercial-grade performance for video delivery and the Web, Content Delivery Networks (CDNs) were introduced. This paper describes the current CDN ecosystem and the forces that have driven its evolution. We outline the different CDN architectures and consider their relative strengths and weaknesses. Our analysis highlights the role of location, the growing complexity of the CDN ecosystem, and their relationship to and implications for interconnection markets.     

The distribution-free newsboy problem: Extensions to the shortage penalty case

In the classical newsboy problem, no cost is assumed if the ordered quantity is less than the demand. However, in reality failure to meet demand is always associated with a penalty. The aim of this work is to extend the analysis of the distribution-free newsboy problem to the case when shortage cost is taken into consideration. The analysis is based on the assumption that only the mean and variance of demand are known, but its particular probability distribution is not. A model is presented for determining both an optimal order quantity and a lower bound on the profit under the worst possible distribution of the demand. The following cases are considered: the single product case, the fixed ordering cost case, the random yield case, and the resource-constrained multi-product case.     

物业管理问题及对策

通过回顾物业管理行业的发展历程，就其作用、必要性和意义，对我国物业管理的现状进行分析，指出所存在的主要问题，结合可持续发展的理念，提出了物业管理行业进一步发展完善的若干对策。     

The accentuated CEO career horizon problem: evidence from international acquisitions

We develop a conceptual model of the career horizon problem of CEOs approaching retirement and discuss its implications on firm risk taking, specifically in engagement in international acquisitions. Based on prospect theory and agency theory, we emphasize the legacy conservation and wealth preservation concerns of CEOs and investigate how their holdings of in‐the‐money unexercised options and firm equity accentuate or mitigate the career horizon problem. The model is tested in the context of international acquisitions with a sample of 293 U.S. firms over a five‐year period (1995–1999). We find that a longer CEO career horizon is associated with a higher likelihood of international acquisitions. We also find that CEOs nearing retirement with high levels of in‐the‐money unexercised options and equity holdings are less likely to engage in international acquisitions than CEOs with low levels of in‐the‐money options and equity holdings. The study raises important considerations about the implications of CEOs' equity and in‐the‐money option holdings on firm risk taking at various stages of their career horizon. Copyright © 2008 John Wiley & Sons, Ltd.     

The storage location assignment problem for outbound containers in a maritime terminal

This paper addresses the storage location assignment problem for outbound containers. The problem is decomposed into two stages. The yard bays and the amount of locations in each yard bay, which will be assigned to the containers bounded for different ships, are determined in the first stage. The exact storage location for each container is determined in the second stage. The problem in the first stage is solved by a mixed integer programming model, while a hybrid sequence stacking algorithm is applied to solve the problem in the second stage. Experimental results show that the proposed approach is effective and efficient in solving the storage location assignment problem for outbound containers.