Absalom: Balancing assembly lines with assignment restrictions

Assembly line balancing problems (ALBPs) arise whenever an assembly line is configured, redesigned or adjusted. An ALBP consists of distributing the total workload for manufacturing products among the work stations along the line. On the one hand, research has focussed on developing effective and fast solution methods for exactly solving the simple assembly line balancing problem (SALBP). On the other hand, a number of real-world extensions of SALBP have been introduced but solved with straight-forward and simple heuristics in many cases. Therefore, there is a lack of procedures for exactly solving such generalized ALBP.In this paper, we show how to extend the well-known solution procedure Salome [Scholl, A., Klein, R., 1997. Salome: A bidirectional branch-and-bound procedure for assembly line balancing. Informs J. Comput. 9 319–334], which is able to solve even large SALBP instances in a very effective manner, to a problem extension with different types of assignment restrictions (called ARALBP). The extended procedure, referred to as Absalom, employs a favorable branching scheme, an arsenal of bounding rules and a variety of logical tests using ideas from constraint programming.Computational experiments show that Absalom is a very promising exact solution approach although the additional assignment restrictions complicate the problem considerably and necessitate a relaxation of some components of Salome.     

Promoting symmetric weight selection in data envelopment analysis: A penalty function approach

Traditionally, data envelopment analysis models assume total flexibility in weight selection, though this assumption can lead to several variables being ignored in determining the efficiency score. Existing methods constrain weight selection to a predefined range, thus removing possible feasible solutions. As such, in this paper we propose the symmetric weight assignment technique (SWAT) that does not affect feasibility and rewards decision making units (DMUs) that make a symmetric selection of weights. This allows for a method of weight restrictions that does not require preference constraints on the variables. Moreover, we show that the SWAT method may be used to differentiate among efficient DMUs.     

Benzene and Toluene Levels Measured with DOAS During Vehicular Restrictions in Beijing

Measurements of atmospheric benzene and toluene were carried out continuously using dif-ferential optical absorption spectroscopy from August 7 to August 28 in Beijing during the period of vehicular restrictions. The correlations between traffic flows and totals of benzene and toluene were studied during the period of vehicular traffic restrictions from August 17 to August 20 and non-traffic restrictions on August 16 and August 21. The correlation coef-ficient was 0.8 between benzene and toluene. And the calculated daily mean value ratios of benzene to toluene were 0.43-0.50. During the period of vehicular restrictions, traffic flows were reduced about 11.8% and the levels of benzene and toluene were reduced by 11.4% and 12.8%, respectively. The vehicle emissions were recognized as the major sources for atmospheric benzene and toluene in Beijing.     

π-σ轨道作用能分解法和限制π轨道作用的几何优化*

简要地介绍能量分解法的发展历史,强调能量分解的特点是给量子化学的计算提供明确的化学意义,介绍本实验室建立的能量分解法和限制轨道作用的几何优化法。 在这两个方法的基础上,论证了π-电子离域是失稳定的;颠倒了经典有机结构理论中基本的因果关系——共轭效应和构象之间的因果关系;为芳香能的计算提供了一个新的模型和新的方法,表明芳香能的计算不再需要参考分子;定量地区别静电作用和电子离域在化学键形成中的作用;定量地讨论取代基效应和张力芳环的扭曲驱动力。     

On Lie p-algebras of cohomological dimension one

We prove that a Lie $p$-algebra of cohomological dimension one is one-dimensional, and discuss related questions.     

矩形掺杂光子晶体中电磁波的模式和缺陷模

利用一维矩形掺杂光子晶体中电磁波横向受限的条件,推导出电磁波在其中各个模式满足的关系式,利用它研究了电磁波各模式的特性.利用特征法研究了电磁波的缺陷模随模式量子数和矩形边长的变化规律,得出了一维矩形掺杂光子晶体缺陷模的新结构.     

一类数字限制集的上、下Assouad维数

设b≥2,D_1,D_2■{0,1,...,b-1},S_1,S_2■N且S_1,S_2不交.记E是由下面(1.1)所确定的数字限制集.本文讨论了E的各种分形维数,主要证明了E的上、下Assouad维数公式.     

Restricting weights in supplier selection decisions in the presence of dual-role factors

One of the uses of data envelopment analysis (DEA) is supplier selection. Weight restrictions allow for the integration of managerial preferences in terms of relative importance levels of various inputs and outputs. As well, in some situations there is a strong argument for permitting certain factors to simultaneously play the role of both inputs and outputs. The objective of this paper is to propose a method for selecting the best suppliers in the presence of weight restrictions and dual-role factors. This paper depicts the supplier selection process through a DEA model, while allowing for the incorporation of decision maker’s preferences and considers multiple factors which simultaneously play both input and output roles. The proposed model does not demand exact weights from the decision maker. This paper presents a robust model to solve the multiple-criteria problem. A numerical example demonstrates the application of the proposed method.     

Effects of volume fraction condition on thermodynamic restrictions in mixture theory

Volume fraction condition is a true constraint that must be taken into consideration in deducing the thermodynamic restrictions of mixture theory applying the axiom of dissipation. For a process to be admissible, the constraints imposed by the volume fraction condition include not only the equation obtained by taking its material derivative with respect to the motion of a given phase, but also those by taking its spatial gradient. The thermodynamic restrictions are deduced under the complete constraints, the results obtained are consistent for the mixtures with or without a compressible phase, and in which the free energy of each phase depends on the densities of all phases.     

Computation of efficient targets in DEA models with production trade-offs and weight restrictions

Recently new models of data envelopment analysis (DEA) were introduced that incorporate production trade-offs between inputs and outputs or based on them weight restrictions. In this paper, we develop a computational procedure suitable for the practical application of such models. We show that the standard two-stage optimisation procedure used in DEA to test the full efficiency of units and identify their efficient targets may work incorrectly in the new models. The modified procedure consists of three stages: the first evaluates the radial efficiency of the unit, the second identifies its efficient target, and the third its reference set of efficient peers. Each stage requires solving one linear program for each unit.