An Interactive Heuristic Approach for Multi-Objective Integer-Programming Problems

An interactive approach to solve the multi-objective integer-programming problem heuristically is described. The approach consists of two main parts. The first is an algorithm to guide the search for a set of weights to the objective functions which would produce the solution most preferred by the decision-maker given a linear utility function. The search area is successively decreased through an interaction process, with the decision-maker using a selection and contraction method. During each stage of this algorithm, a number of single integer-programming problems are solved heuristically. The motivation for this approach, along with some computational experimentation, is provided.     

一种有交易费用的交互式组合证券投资方法

本基于乘积最大化准则，提出一种新的交互式组合证券投资方法，即将不可微的双目标规划问题转化为可微的单目标规划问题。该方法可以充分考虑投资的要求，在考虑交易费用的前提下，在整个投资方案达到投资要求底限的同时，实现收益和风险的权衡。     

A Note on Multiplicative Utility in Interactive Project Selection

In an earlier paper, the authors presented an interactive method for project selection. The method used additive utilities. This note briefly reports the appropriate modifications for using multiplicative utilities.     

Discrete Multiattribute Utility Approach to Project Selection

The purpose of this paper is to review various structures of the project-selection problem with discrete multiattribute utility. The approach of maximizing the utility for project selection is discussed where the utility function cannot be measured on a continuous scale. The review includes reference to models of uncertainty versus certainty, and to models assuming the existence of dependence and complementary relations among projects versus independent projects. Project selection in hierarchical organizations with a large number of projects and group decisions is also referred to. The various types of models are formulated and analysed, including applications in the areas of water resources, R&D and nuclear plant location. Finally, directions for future research are suggested.     

An Interactive Multiple Criteria Approach to Ranking Alternatives

In this paper we are concerned with ranking various orderings of a set of alternatives to a composite order as a multiple criteria problem. The orderings (called preference orderings) can be real preference orderings or any natural orderings. The objective is to find the most preferred order of the decision maker using the preference orderings as criteria.In principle, the problem can be formulated as a multiple objective linear programming problem using the model of Bowman and Colantoni and then solved with the interactive method proposed by Zionts and Wallenius. However, the fact that we are dealing with integer variables prohibits us from applying this approach as such. We discuss the problem formulation and propose a modified approach to that of Zionts and Wallenius for solving the problem.     

Combined MCDA–IP Approach for Project Selection in the Electricity Market

The European policy target of substantially increasing the share of renewable energy in electricity generation, in combination with national subsidization support schemes, has strongly motivated private investors towards this business sector. In Greece, this interest is particularly apparent in the case of wind energy exploitation, due to a favourable legislative framework and the important wind potential available in several Greek regions. In such endowed regions, a very high number of applications were submitted to the competent authority, most of which compete for the same most attractive (windy) sites. The selection among these applications is a multicriteria problem that has been solved with the support of a Decision-Aid tool combining the multicriteria classification method ELECTRE-TRI with Integer Linear Programming. The developed approach takes into account both, the performances of the applications to the evaluation criteria, as well as a number of technical and policy constraints.     

一种交互式遗传算法生成带主题乐曲的方法

在算法作曲领域中,遗传算法由于其不依赖于问题参数本身及具有较好的全局最优解等特性,被很多人应用于乐曲创作中,但是生成的乐曲也具有无主题和盲目性等缺陷.为解决这一问题,在适应度函数中定义了几条规则使得乐曲向有利于生成主题的方向进化,再通过人工评价使所选出的乐曲更能符合人们的欣赏习惯.实验结果表明,使用基于规则的交互式遗传算法所生成的带主题的乐曲能够满足人们的欣赏要求.     

An Interactive Approach for Choosing the Best of a Set of Alternatives

In this paper we address the problem of choosing the most preferred alternative among a large number of alternatives where each alternative is defined by multiple criteria. We assume that the decision maker has a quasiconcave utility function. We develop an exact approach that combines the ideas that have appeared in the literature regarding the use of different types of dummy alternatives in conjunction with real alternatives. Our experimental results indicate that the new approach is comparable to leading existing approaches.     

An Interactive,Graphical Approach to Linear Financial Models

Early attempts to utilize linear algebraic (L.P.) techniques in financial planning met with little success. This was probably due to a misunderstanding of the process by which financial and corporate plans were formulated. The planning process is now better understood and the use of computer-based models is well accepted. However current modelling systems perform only simple arithmetic evaluations. There is a prima facie case for re-examining linear algebraic methods to exploit the considerable amount of information which is available within a plan. This paper describes the work done in the South of Scotland Electricity Board to develop an interactive financial modelling system.     

Stochastic MOLP with Incomplete Information: An Interactive Approach with Recourse

Numerous multiobjective linear programming (MOLP) methods have been proposed in the last two decades, but almost all for contexts where the parameters of problems are deterministic. However, in many real situations, parameters of a stochastic nature arise. In this paper, we suppose that the decision-maker is confronted with a situation of partial uncertainty where he possesses incomplete information about the stochastic parameters of the problem, this information allowing him to specify only the limits of variation of these parameters and eventually their central values. For such situations, we propose a multiobjective stochastic linear programming methodology; it implies the transformation of the stochastic objective functions and constraints in order to obtain an equivalent deterministic MOLP problem and the solving of this last problem by an interactive approach derived from the STEM method. Our methodology is illustrated by a didactical example.     

基于直觉模糊二元语义交互式群决策的技术创新项目选择

为适应全球经济一体化的快速发展,企业应选择最优的技术创新项目,从而提升其竞争力。首先定义了直觉模糊二元语义,探讨了将其区间化的方法,建立了直觉模糊二元语义与区间模糊二元语义之间的联系。接着重新定义了直觉模糊二元语义的距离和相似度,给出了群决策的集结算子。通过集结决策者的意见和进行交互式决策,使得群体的决策意见达到满意的一致性水平。最后以技术创新项目选择为例说明了本文提出的方法。     

A Network-Flow Algorithm for Project Selection

A simple network-flow algorithm is described for solving a class of problems, with various applications, including that of project selection. The algorithm should have wide appeal since no prior knowledge of network algorithms is required, and the familiar activity-on-node type of network provides the starting point for the algorithm. This work is an extension of an approach recently proposed by H. P. Williams.     

Natural Selection: Interactive Subset Creation

Abstract

Visualization is a critical technology for understanding complex, data-rich systems. Effective visualizations make important features of the data immediately recognizable and enable the user to discover interesting and useful results by highlighting patterns. A key element of such systems is the ability to interact with displays of data by selecting a subset for further investigation. This operation is needed for use in linked views systems and in drill-down analysis. It is a common manipulation in many other systems and is as ubiquitous as selecting icons in a desktop graphical user interface (GUI). It is therefore surprising to note that little research has been done on how selection can be implemented. This article addresses this omission, presenting a taxonomy for selection mechanisms and discussing the interactions between branches of the taxonomy.     

项目投资的交互式决策分析

本文以某个企业技改项目投资决策为例,给出了一个交互式多目标决策过程.该过程充分考虑了企业进行决策时的实际情况及环境和人的主观偏好,所得结果更合理.     

投资项目选择的风险评价AHP模型及其应用

论述了投资项目选择问题的重要性 ,对常用的投资项目选择方法进行了综述分析 ,探讨了投资项目选择的风险评价指标体系和层次分析法的基本原理 ,提出了投资项目选择的风险评价层次分析模型 ,并以实例说明了如何将层次分析法应用于投资项目选择的风险评价问题 .     

Marriage Partner Selection in Kuwait: An Analytical Hierarchy Process Approach

The decision to marry is one of the most critical decisions in young ladie' lives where wrong choices may have adverse effects. This study investigates this issue in developing countries using the small state of Kuwait as a manageable case study. This research utilizes the analytical hierarchy process (AHP) due to the multiplicity of objectives. Women from different ethnic, religious, and residential backgrounds were surveyed. The problem considers eight criteria and four alternatives (male candidates). It was found from the study that the most preferred criteria are personality, followed by marital status and religious status, respectively.     

An Operations Research Approach to the Problem of the Sugarcane Selection

Selection for superior clones is the most important aspect of sugar cane improvement programs, and is a long and expensive process. While studies have investigated different components of selection independently, there has not been a whole system approach to improve the process. This study observes the problem as an integrated system, where if one parameter changes the state of the whole system changes. A computer based stochastic simulation model that accurately represents the selection was developed. This paper describes the simulation model, showing its accuracy as well as how a combination of dynamic programming and branch and bound can be applied to the model to optimise the selection system, giving a new application of these techniques. The model can be directly applied to any region targeted by sugarcane breeding programs or to other clonally propagated crops.     

An Interactive Algorithm for Multi-objective Route Planning

We address the route selection problem for Unmanned Air Vehicles (UAV) under multiple objectives. We consider a general case for this problem, where the UAV has to visit several targets and return to the base. We model this problem as a combination of two combinatorial problems. First, the path to be followed between each pair of targets should be determined. We model this as a multi-objective shortest path problem. Additionally, we need to determine the order of the targets to be visited. We model this as a multi-objective traveling salesperson problem (MOTSP). The overall problem is a combination of these two problems, which we define as a generalized MOTSP. We develop an exact interactive approach to identify the best paths and the best tour of a decision maker under a linear utility function.     

R&D Project Selection in a Multidimensional Environment: A Practical Approach

This paper investigates the R&D project selection problem within government departments. The Department of National Defence is taken as a case in point. The multidimensional character of the problem is detailed, and existing methods for priority allocation are briefly surveyed. Two basic models for selecting projects are described. One of these, the ordinal intersection method, was found to be the most appropriate for the actual problem settings investigated. An illustrative example is given, and concluding remarks are made.