From the Publisher:
This book explores the meta-heuristics approach called tabu search, which is dramatically changing our ability to solve a hostof problems that stretch over the realms of resource planning,telecommunications, VLSI design, financial analysis, scheduling, spaceplanning, energy distribution, molecular engineering, logistics,pattern classification, flexible manufacturing, waste management,mineral exploration, biomedical analysis, environmental conservationand scores of other problems. The major ideas of tabu search arepresented with examples that show their relevance to multipleapplications. Numerous illustrations and diagrams are used to clarifyprinciples that deserve emphasis, and that have not always been wellunderstood or applied. The book's goal is to provide ''hands-on' knowledge and insight alike, rather than to focus exclusively eitheron computational recipes or on abstract themes. This book is designedto be useful and accessible to researchers and practitioners inmanagement science, industrial engineering, economics, and computerscience. It can appropriately be used as a textbook in a masterscourse or in a doctoral seminar. Because of its emphasis on presentingideas through illustrations and diagrams, and on identifyingassociated practical applications, it can also be used as asupplementary text in upper division undergraduate courses. 

Finally, there are many more applications of tabu search than canpossibly be covered in a single book, and new ones are emerging everyday. The book's goal is to provide a grounding in the essential ideasof tabu search that will allow readers to create successfulapplications of their own. Along with the essentialideas,understanding of advanced issues is provided, enabling researchers togo beyond today's developments and create the methods of tomorrow.

Tabu Search

The large-scale organization of metabolic networks

In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

The metabolic network of the catabolic, energy and biosynthetic metabolism of Escherichia coli is a paradigmatic case for the large genetic and metabolic networks that functional genomics efforts are beginning to elucidate. To analyse the structure of previously unknown networks involving hundreds or thousands of components by simple visual inspection is impossible, and quantitative approaches are needed to analyse them. We have undertaken a graph theoretical analysis of the E. coli metabolic network and find that this network is a small-world graph, a type of graph distinct from both regular and random networks and observed in a variety of seemingly unrelated areas, such as friendship networks in sociology, the structure of electrical power grids, and the nervous system of Caenorhabditis elegans. Moreover, the connectivity of the metabolites follows a power law, another unusual but by no means rare statistical distribution. This provides an objective criterion for the centrality of the tricarboxylic acid cycle to metabolism. The small-world architecture may serve to minimize transition times between metabolic states, and contains evidence about the evolutionary history of metabolism.

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The small world inside large metabolic networks

As the details of the chemical transformations in metabolism have become increasingly clear, and the enzymes catalysing many of the reactions have been characterized, it is understandable that biochemists should want to explain at the molecular level the metabolic homeostasis observed at the physiological level. How are the rates of synthesis and degradation of metabolites kept in close balance over a very wide range of external conditions without catastrophic rises or falls in the metabolite concentrations? The discoveries of feedback inhibition, co-operativity and covalent modification in enzymes, and of mechanisms for the control of enzyme synthesis and degradation, have disclosed a repertoire of molecular effects that potentially alter the fluxes in metabolic pathways. With such a range of effects to choose from, it is not surprising that disputes arise over explanations for the changes in flux through particular pathways under given circumstances. Since the explanations are usually verbal and qualitative, discrimination between different explanations, or assessment of their adequacy, is difficult. More recently, several groups have attempted theoretical analysis of the potential of these different molecular mechanisms to contribute to the control of metabolic flux. Since these theories can be given a mathematical formulation, they can be used in combination with appropriate experimental measurements to provide quantitative explanations and, potentially, predictions. The theories have often been controversial. Matters at issue have included the extent to which it is feasible to perform experiments to obtain the necessary data, the adequacy of the theories for making useful predictions, and the degree to which the quantitative measures of the theories do actually capture the relevant aspects of regulation and control. To some extent, this is a matter of semantics; a mathematical theory is more explicit about its underlying assumptions and the meaning of its statements, but regulation and control are two terms that have been used without strict adherence to any agreed definition in many different contexts (as noted in [1]). It is therefore inevitable that some will find that the use of these terms in the context of a mathematical theory places a narrower construction on them than they would like. These theories all include a form of sensitivity analysis; that is, the magnitude of the effect of some small change in a parameter (such as an enzyme activity) on a metabolic system property (such as the flux or the concentration of a metabolite) is mathematically related to the properties of the components of the system. Sensitivity analysis is widely used for analogous problems in other fields, including economics, ecology [2], engineering [3] and chemical kinetics [4-6]. Its application in biochemistry was pioneered by Higgins [7], but three variants subsequently arose: Metabolic Control Analysis, Biochemical Systems Theory and Crabtree and Newsholme's 'flux-oriented' theory (the term used in [8]). It is not possible to give a succinct account of the differences between the approaches, which is a controversial area [9-18] even though the underlying mathematics is equivalent to a considerable extent. One area of difference is the choice of the type of parameter that is changed for the determination of sensitivities. In Metabolic Control Analysis, enzyme concentration (or activity) is usually chosen; the response to an external modifier of a metabolic pathway is derived from the resulting sensitivities. In Biochemical Systems Theory [19-25], the primary parameters for the sensitivities are the 'rate constants' for synthesis and degradation of metabolite pools. Savageau has given many reasons for this choice of parameter; Cornish-Bowden has articulated some of the problems with it [15]. Although using these 'rate constants' simplifies the analysis procedures within Biochemical Systems Theory, there is not a one-to-one relationship between them and the enzymes of the system, which can create a slight complication in determining the sensitivity to variation of an enzyme activity. Savageau's theory is part of an integrated system for stability analysis and simulation, in addition to sensitivity analysis. Crabtree and Newsholme's theory [8,10,26-30] is intermediate between the two others, and the primary sensitivities are to an external modifier (a hypothetical one if necessary), but its mathematical development is less rigorous. In this review, I shall concentrate on Metabolic Control Analysis. This is because, apart from considerations of space, approximately two-thirds of the literature citations of theories of metabolic regulation in the past 5 years have been to Metabolic Control Analysis. This may relate to perceived ease of use, which has been compared using the different approaches on the same set of experimental results [31]. In the following review, I will not give a complete derivation and description of the basic concepts of Metabolic Control Analysis; clear accounts can be found in previous articles and reviews [9,32-39]. Instead I will try to indicate areas of disagreement, the scope of the basic theory and where it has been modified or extended, and recent approaches to experimental applications.

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Metabolic control analysis: a survey of its theoretical and experimental development.

Analysis of an inventory system with exponential partial backordering

The problem of the optimal biobjective spanning tree

https://isiarticles.com/bundles/Article/pre/pdf/2835.pdf

Policies for inventory/distribution systems: The effect of centralization vs. decentralization

In this paper, an economic order quantity inventory model is analyzed, considering that the unit cumulative holding cost has two significant components: a fixed cost which represents the cost of accommodating the item in the warehouse and a variable cost given by a potential function of the length of time over which the item is held in stock. Shortages are allowed and, during the stockout period, only a fraction of demand is partially backordered. The backordering cost includes a fixed cost and a cost linearly dependent on the length of time for which backorder exists. A solution procedure is developed for determining the optimal inventory policy. Moreover, to illustrate the effects of some parameters on the optimal policy and the minimum total inventory cost, a numerical study is developed.

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Joaquín Sicilia

Papers

Analysis of an inventory system with exponential partial backordering

The problem of the optimal biobjective spanning tree

Policies for inventory/distribution systems: The effect of centralization vs. decentralization

Analysis of an EOQ inventory model with partial backordering and non-linear unit holding cost

A new characterization for the dynamic lot size problem with bounded inventory