Teaching scenario planning: Lessons from practice in academe and business

In this paper, we engage with O’Brien’s [O’Brien, F.A., 2004. Scenario planning – lessons for practice from teaching and learning. European Journal of Operational Research 152, 709–722] identification of both pitfalls in teaching scenario planning and proposed remedies for these. We consider these remedies in relation to our own experience – based on our practice in both the academic and business arenas – and we highlight further pitfalls and proposed remedies. Finally, we propose the use of “hard” multi-attribute decision analysis as a complement to “soft” scenario planning, in order to allow a more formal method of strategy evaluation against a range of constructed scenarios, This approach is intended to remedy biases that are associated with holistic evaluations – such as lexicographic ranking – where undue attention is paid to particular strategic objectives at the expense of others. From this discussion, we seek to contribute to cumulative refinement of the scenario process.     

长株潭地区可持续发展的综合评价——基于“两型社会”建设的视角

参照国内外现有的可持续发展指标体系,基于"两型社会"建设的视角,根据长株潭地区的具体特征以及数据的可得性,建立了包含经济社会与资源环境2个一级指标21个二级指标的长株潭可持续发展指标体系,并采用2000到2011年年度数据对长株潭地区可持续发展进行了评估与分析.研究结果显示,长株潭地区的生态环保指标综合得分已从2004年前的小于经济社会指标综合得分变为当前的大于经济社会指标综合得分;地区可持续发展度已从2000年前的非可持续逐渐过渡到现在的接近高可持续性,意味着"两型社会"第一阶段的各项目标任务已基本完成.但产业转型难将会成为长株潭整体辐射区生态环境优化的重要瓶颈.     

Numerical optimisation for induction heat treatment processes

This paper aims at introducing new approaches for designing and optimising induction heat treatment processes. Although the final objectives of induction heating processes may deal with some specific mechanical or metallurgical properties for manufactured parts, we shall primarily focus here on achieving an accurate control of temperature distribution and evolution in the Heat Affected Zone (HAZ). This objective can be formalised as a classical optimisation problem: we seek to minimise a cost function which measures the difference between computed and goal temperatures – along with some constraints on process parameters. We deal here with both zero-order algorithms – using a method based on Efficient Global Optimization algorithm which is an optimisation procedure assisted by a meta model – as well as first-order algorithms. These algorithms have been coupled with 2-D and 3-D finite element models developed in our laboratory; this model is based on a coupling procedure between Maxwell equations and heat transfer models, and has been extended to mechanical and metallurgical computations.     

Measures of inefficiency in data envelopment analysis and stochastic frontier estimation

This paper discusses recent work in developing scalar measures of inefficiency which (a) comprehend all inefficiencies, including non-zero slacks, and (b) are readily interpretable and easily used in a wide variety of contexts. The opening section of the paper discusses some of the varied contexts in which uses of DEA are now being reported. This provides background for some of these measures. The closing section turns to simulation studies of DEA-regression combinations and possible inefficiency measures. Serious problems of bias in SF (Stochastic Frontier) regression approaches are identified. Extensions and modifications are suggested which can make a development of other inefficiency measures worthwhile for SF extensions to input-specific and multiple output evaluations.     

New advances in economic modelling and evaluation of environmental issues

This paper gives an overview of recent progress made in modelling economic environmental systems and in environmental policy analysis. In the modelling part attention will be given to new integrating frameworks offered inter alia by materials balance approaches, especially in the context of linkages between physical environmental phenomena and economic production and valuation. These can be relevant for studying materials-product chains, multisectoral materials flows, or even multiple use of complex ecosystems. Modern approaches will be dealt with, such as analysis for sustainable development, and ways of incorporating scenario experiments in environmental modelling approaches. In the context of sustainable development, modelling of multiple use of ecosystems and of spatial dimensions is also discussed. In the last part of the paper new advances in the area of environmental policy analysis will be dealt with. The main focus will be on methods for addressing uncertainty in evaluating environmental policy strategies, in particular fuzzy information and the use of meta-analysis.     

Multiple taxicab correspondence analysis

We compare the statistical analysis of multidimensional contingency tables by multiple correspondence analysis (MCA) and multiple taxicab correspondence analysis (MTCA). We will show in this paper: First, MTCA and MCA can produce different results. Second, taxicab correspondence analysis of a Burt table is equivalent to centroid correspondence analysis of the indicator matrix. Third, along the first principal axis, the projected response patterns in MTCA will be clustered and the number of cluster points is less than or equal to 1+ the number of variables. Fourth, visual maps produced by MTCA seem to be clearer and more readable in the presence of rarely occurring categories of the variables than the graphical displays produced by MCA. Two well known data sets are analyzed.     

Job scheduling with forbidden setups and two objectives using genetic algorithms and penalties

One of the most important tasks in service and manufacturing systems is how to schedule arriving jobs such that some criteria will be satisfied. Up to now there have been defined a great variety of scheduling problems as well as corresponding models and solution approaches. Most models suffer from such more or less restrictive assumptions like single machine, unique processing times, zero set-up times or a single criterion. On the other hand some classical approaches like linear or dynamic programming are practicable for small-size problems only. Therefore over the past years we can observe an increasing application of heuristic search methods. But scheduling problems with multiple machines, forbidden setups and multiple objectives are scarcely considered. In our paper we apply a Genetic Algorithm to such a problem which was found at a continuous casting plant. Because of the forbidden setups the probability for a random generated schedule to be feasible is nearly zero. To resolve this problem we use three kinds of penalties, a global, a local and a combined approach. For performance investigations of these penalty types we applied our approaches to a real world test instance with 96 jobs, three machines and two objectives. We tested five different penalty levels with 51 independent runs to evaluate the impact of the penalties.     

A comparison of multiple criteria analysis techniques for water resource management

Multiple criteria analysis (MCA) is a framework for evaluating decision options against multiple criteria. Numerous techniques for solving an MCA problem are available. This paper applies MCA to six water management decision problems. The MCA methods tested include weighted summation, range of value, PROMTHEE II, Evamix and compromise programming. We show that different MCA methods were in strong agreement with high correlations amongst rankings. In the few cases where strong disagreement between MCA methods did occur it was due to presence of mixed ordinal-cardinal data in the evaluation matrix. The results suggest that whilst selection of the MCA technique is important more emphasis is needed on the initial structuring of the decision problem, which involves choosing criteria and decision options.     

A multiple criteria decision making approach to manure management systems in the Netherlands

The intensification of livestock operations in the last few decades has resulted in an increased social concern over the environmental impacts of livestock operations and thus making appropriate manure management decisions increasingly important. A socially acceptable manure management system that simultaneously achieves the pressing environmental objectives while balancing the socio-economic welfare of farmers and society at large is needed. Manure management decisions involve a number of decision makers with different and conflicting views of what is acceptable in the context of sustainable development. This paper developed a decision-making tool based on a multiple criteria decision making (MCDM) approach to address the manure management problems in the Netherlands. This paper has demonstrated the application of compromise programming and goal programming to evaluate key trade-offs between socio-economic benefits and environmental sustainability of manure management systems while taking decision makers’ conflicting views of the different criteria into account. The proposed methodology is a useful tool in assisting decision makers and policy makers in designing policies that enhance the introduction of economically, socially and environmentally sustainable manure management systems.     

The exploratory analysis of qualitative variables by means of three-way analysis of two types of quantification matrices

A comparison is made between a number of techniques for the exploratory analysis of qualitative variables. The paper mainly focuses on a comparison between multiple correspondence analysis (MCA) and Gower's principal co-ordinates analysis (PCO), applied to qualitative variables. The main difference between these methods is in how they deal with infrequent categories. It is demonstrated that MCA solutions can be dominated by infrequent categories, and that, especially in such cases, PCO is a useful alternative to MCA, because it tends to downweight the influence of infrequent categories. Apart from studying the difference between MCA and PCO, other alternatives for the analysis of qualitative variables are discussed, and compared to MCA and PCO.     

Modeling sustainability transitions on complex networks

There has been renewed interest in sociotechnical systems in the context of transitioning to a more sustainable society. While gains have been made in the qualitative understanding of sustainable transitions and sociotechnical systems, these approaches have not been well‐operationalized. Given the importance of meeting future energy and environmental policy targets, there is need to develop predictive techniques and more robust methods to quantify and analyze sociotechnical systems undergoing rapid change and uncertainty due to sustainability pressures. Sustainability transitions depend on large‐scale diffusion of technological and behavioral innovations on physical and virtual networked systems. Transitions can therefore be viewed as a subclass of diffusion phenomenon and subject to a range of mathematical and computational methods. We review, categorize, and critically assess methodological and theoretical approaches that integrate different aspects of sustainability, innovation, and complexity. We argue that these approaches should be adapted to improve our understanding of the behavior and dynamics of a broad range of sociotechnical systems to meet sustainability objectives. We therefore also make the conceptual link between complexity and sustainability as complimentary fields of research to inform policy and decision making to achieve more sustainable outcomes. © 2014 Wiley Periodicals, Inc. Complexity 19: 8–22, 2014     

Exploiting nested inequalities and surrogate constraints

The exploitation of nested inequalities and surrogate constraints as originally proposed in Glover [Glover, F., 1965. A multiphase-dual algorithm for the zero–one integer programming problem. Operations Research 13, 879–919; Glover, F., 1971. Flows in arborescences. Management Science 17, 568–586] has been specialized to multidimensional knapsack problems in Osorio et al. [Osorio, M.A., Glover, F., Hammer, P., 2002. Cutting and surrogate constraint analysis for improved multidimensional knapsack solutions. Annals of Operations Research 117, 71–93]. We show how this specialized exploitation can be strengthened to give better results. This outcome results by a series of observations based on surrogate constraint duality and properties of nested inequalities. The consequences of these observations are illustrated by numerical examples to provide insights into uses of surrogate constraints and nested inequalities that can be useful in a variety of problem settings.     

Constrained group balancing: Why does it work

We consider a problem where a set of objects possessing multiple attributes must be partitioned into a certain number of groups so that the groups are as balanced as possible with respect to the number of objects possessing each attribute. This multi-criteria decision problem arises in a variety of practical applications, ranging from assigning students to study groups to designing level schedules for JIT assembly lines. A direct approach, enforcing balance through hard constraints, may lead to infeasibility, but works well in practice. We analyze this phenomenon from the worst-case and empirical perspectives, as well as through an in-depth analysis of one representative practical application – the design of student groups at the Rotman School of Management, University of Toronto. The goals of the analysis are to understand what classes of balancing problems may contain infeasible instances and how prevalent such instances are within these classes, as well as to synthesize practical managerial insights that a decision maker could follow in order to increase the chances that balanced groups can be found.     

Reply to the note on article “The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees”

In a very recent note by Gao and Ni [B. Gao, M.F. Ni, A note on article “The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees”, European Journal of Operational Research, in press, doi:10.1016/j.ejor.2007.10.0381], they argued that Yen’s combination rule [J. Yen, Generalizing the Dempster–Shafer theory to fuzzy sets, IEEE Transactions on Systems, Man and Cybernetics 20 (1990) 559–570], which normalizes the combination of multiple pieces of evidence at the end of the combination process, was incorrect. If this were the case, the nonlinear programming models we proposed in [Y.M. Wang, J.B. Yang, D.L. Xu, K.S. Chin, The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees, European Journal of Operational Research 175 (2006) 35–66] would also be incorrect. In this reply to Gao and Ni, we re-examine their numerical illustrations and reconsider their analysis of Yen’s combination rule. We conclude that Yen’s combination rule is correct and our nonlinear programming models are valid.     

Transparent prioritisation,budgeting and resource allocation with multi-criteria decision analysis and decision conferencing

Managers in both for-profit and not-for-profit organisations continually face the task of allocating resources by balancing costs, benefits and risks and gaining commitment by a wide constituency of stakeholders to those decisions. This task is complex and difficult because many options are present, benefits and risks are rarely expressed as single objectives, multiple stakeholders with different agendas compete for limited resources, individually optimal resource allocations to organisational units are rarely collectively optimal, and those dissatisfied with the decisions taken may resist implementation. We first explain three current approaches to resource allocation taken from corporate finance, operational research and decision analysis, and we identify a common mistake organisations make in allocating resources. The paper then presents a technical process, multi-criteria portfolio analysis, for balancing the conflicting elements of the problem, and a social process, decision conferencing, which engages all the key players during the modelling process, ensuring their ownership of the model and the subsequent implementation. This socio-technical process improves communication within the organisation, develops shared understanding of the portfolio and generates a sense of common purpose about those projects that will best realise the organisation’s objectives. The paper concludes with lessons we have learned from actual practice. The authors want to thank Allergan and FCT (Portuguese Science Foundation) for their support.     

Integrated data envelopment analysis: Global vs. local optimum

Chiou et al. (2010) (A joint measurement of efficiency and effectiveness for non-storable commodities: integrated data envelopment analysis approaches. European Journal of Operational Research 201, 477–489) propose an integrated data envelopment analysis model in measuring decision making units (DMUs) that have a two-stage internal network structure with multiple inputs, outputs, and consumptions. They claim that any optimal solutions determined by their DEA model are a global optimum, not a local optimum. We show that such a conclusion is a false statement due to their misuse of Hessian matrix in examining the concavity of the objective function, and their DEA model is actually a non-convex optimization problem. As a result, their DEA model is unusable in practice due to a lack of efficient algorithm for this particular non-convex DEA model. We further show that Chiou et al.’s (2010) model is a special case of a well-known two-stage network DEA model, and it can be transformed into a parametric linear program for which an approximate global optimal solution can be obtained by solving a sequence of linear programs in combination with a simple search algorithm.     

Searching for psychologically stable solutions of multiple criteria decision problems

In interactive decision making, a choice behavior of the decision maker may differ depending on proximity of a current solution to satisfactory values of objectives. An interactive approach proposed in this paper allows the decision maker to use different search principles depending on his/her perception of the achieved values of objectives and trade-offs. While an analysis of the values of objectives may guide the initial search for a final solution, it can be replaced by trade-off evaluations at some later stages. Such an approach allows the decision maker to change search principles, and to identify a psychologically stable solution to the multiple criteria decision problem.     

Nonessential objectives within network approaches for MCDM

In Gal and Hanne [Eur. J. Oper. Res. 119 (1999) 373] the problem of using several methods to solve a multiple criteria decision making (MCDM) problem with linear objective functions after dropping nonessential objectives is analyzed. It turned out that the solution does not need be the same when using various methods for solving the system containing the nonessential objectives or not. In this paper we consider the application of network approaches for multicriteria decision making such as neural networks and an approach for combining MCDM methods (called MCDM networks). We discuss questions of comparing the results obtained with several methods as applied to the problem with or without nonessential objectives. Especially, we argue for considering redundancies such as nonessential objectives as a native feature in complex information processing. In contrast to previous results on nonessential objectives, the current paper focuses on discrete MCDM problems which are also denoted as multiple attribute decision making (MADM).     

Developing new formulations and relaxations of single stage capacitated warehouse location problem (SSCWLP): Empirical investigation for assessing relative strengths and computational effort

In literature, single/multistage warehouse location problems have been attempted by Geoffrion and Graves [A.M. Geoffrion, G.W. Graves, Multicommodity distribution system design by Benders decomposition, Management Science 2 (1974) 82–114] and Sharma [R.R.K. Sharma, Modeling a fertilizer distribution system, European Journal of Operational Research 51 (1991) 24–34] among others and they have given completely different formulations. We use the formulation style given by Sharma and Sharma [R.R.K. Sharma, K.D. Sharma, A new dual based procedure for the transportation problem, European Journal of Operational Research 122 (3) (2000) 96–109] to develop variety of constraints that link real and 0–1 integer variables; thus developing many formulations of single stage capacitated warehouse location problem (SSCWLP). We relax the integer constraints on 0–1 variables to obtain their relaxations.     

Requiem for the Miller–Tucker–Zemlin subtour elimination constraints?

The Miller–Tucker–Zemlin (MTZ) Subtour Elimination Constraints (SECs) and the improved version by Desrochers and Laporte (DL) have been and are still in regular use to model a variety of routing problems. This paper presents a systematic way of deriving inequalities that are more complicated than the MTZ and DL inequalities and that, in a certain way, “generalize” the underlying idea of the original inequalities. We present a polyhedral approach that studies and analyses the convex hull of feasible sets for small dimensions. This approach allows us to generate generalizations of the MTZ and DL inequalities, which are “good” in the sense that they define facets of these small polyhedra. It is well known that DL inequalities imply a subset of Dantzig–Fulkerson–Johnson (DFJ) SECs for two-node subsets. Through the approach presented, we describe a generalization of these inequalities which imply DFJ SECs for three-node subsets and show that generalizations for larger subsets are unlikely to exist. Our study presents a similar analysis with generalizations of MTZ inequalities and their relation with the lifted circuit inequalities for three node subsets.