Multi-objective linear programming with partial ranking of objectives

This paper is concerned with multi-objective linear programming problems in which the objective functions can be partially ranked. We represent the set of admissible weight vectors by a system of linear constraints and solve for the policy most likely to be optimum. If each admissible weight vector has the same probability of being correct, the optimum policy maximizes the hypervolume of the polytope of weight vectors having this policy as a solution. The proposed algorithm requires the enumeration of the subset of admissible efficient solutions of a multi-objective linear program. For each admissible solution, we estimate the ratio of the volumes of the corresponding polytope of weight vectors and the polytope of all admissible weight vectors. An algorithm is outlined for numerical integration using the Monte Carlo method. The model is extended to the case where several objectives are expressed as linear constraints with multiple parameter vectors and there is uncertainty about the weighting of these parameters. A numerical example is provided.     

Optimal investment models with vintage capital: Dynamic programming approach

The dynamic programming approach for a family of optimal investment models with vintage capital is here developed. The problem falls into the class of infinite horizon optimal control problems of PDE’s with age structure that have been studied in various papers (12, 11, 33 and 35) either in cases when explicit solutions can be found or using Maximum Principle techniques.     

Mathematical models for decision-making in planning drug abuse control programs

In this paper, a framework for systematizing the different applications of decision-making models to the control of drug abuse is first presented. Next, the available literature on the topic is used to exemplify as many as possible of the elements of the framework presented. Finally, extensions of the current state of the field in the direction of disaggregated and of dynamic models are presented.     

Testable implications of general equilibrium models: An integer programming approach

Focusing on the testable revealed preference restrictions on the equilibrium manifold, we show that the rationalizability problem is NP-complete. Subsequently, we present a mixed integer programming (MIP) approach to characterize the testable implications of general equilibrium models. Attractively, this MIP approach naturally applies to settings with any number of observations and any number of agents. This is in contrast with existing approaches in the literature. We also demonstrate the versatility of our MIP approach in terms of dealing with alternative types of assignable information. Finally, we illustrate our methodology on a data set drawn from the US economy. In this application, an important focus is on the discriminatory power of the rationalizability tests under study.     

Building,coding and programming 3D models via a visual programming environment

This paper presents the findings of a study conducted in the state-funded Infant, Primary and Secondary School Santísima Trinidad in Salamanca. The main objectives of the research were, to evaluate the use of the visual programming environment, Lego Education WeDo, in natural science and to know the benefits of the use of this tool to teach abstract concepts, solve problems and motivate students. In order to achieve these objectives, we used the case study method since we focused on individuals who represented the phenomenon of our interest, and explored and investigated in depth the phenomenon in its natural context bounded by time and space. In the research were involved a teacher and fifty-two students of 4th grade of primary education. The study found that the project developed was effective to help students to achieve the learning objectives of the unit, and also to begin building, coding and programming 3D models. The research showed the teacher’ fundamental role as a guide and students’ active role as builders, programmers, or presenters. There were evidences of the possibilities offered to acquire the skills of critical thinking, creative thinking, problem solving, reflection, collaboration, communication, and time management. Due to the positive results obtained in this study, it is recommended to incorporate computational thinking in primary education and in core content areas since it is fundamental in the current society.     

Qualitative discrete multiple criteria choice models in regional planning

The paper provides a concise review of evaluation methods for decision problems in which qualitative data is involved. Special attention is paid to a new qualitative evaluation method: the regime method. An application of the regime method is given in the field of multiregional conflict analysis.     

The role of prior information in updating regional input-output models

The research reported here focuses on several issues: (1) the specification and measurement of errors in single region input-output models and their impacts on the construction of new models from survey and nonsurvey sources and the updating of existing models; (2) the problems of errors in input-output models when the latter are incorporated into more extensive social accounting systems and (3) linkages between the aggregation issue, error analysis and micro-to-macro modelling within an input-output framework. Empirical analysis is conducted on many of these issues by reference to the State of Washington input-output models for 1963, 1967 and 1972.     

Comparative statics in dynamic programming models with an application to job search

This paper presents a technique for qualitative comparative statics analysis in dynamic programming models. Let the value function υ be the fixed point of a contraction mapping which depends differentiably on some exogenous parameter θ. Ten the derivative of υ with respect to θ exists and is also the fixed point of a contraction mapping. Since this derivative is the fixed point of a contraction mapping, its qualitative properties can be investigated using mathematical induction. This comparative statics methodology is illustrated with an application to a model of job search.     

New ways to profit from a feasibility study

Contrary to popular opinion, a feasibility study should do more than simply indicate a "go/no-go" decision says this author. What it can do is measure how an institution can go about raising those big dollars.     

A literature review of decision-making models and approaches for partner selection in agile supply chains

The paper reviews the literature on supply partner decision-making published between 2001 and 2011, a period that has seen a significant increase in work published in this field. The progress made in developing new models and methods that can be applied to this task is assessed in the context of the previous literature. Particular attention is given to those methods that are especially relevant for use in agile supply chains. The paper uses a classification framework that enables models intended for similar purposes to be compared and tracked over time. It is also used to identify a number of gaps in the literature. The findings highlight an on-going need to develop methods that are able to meet the combination of qualitative and quantitative objectives that are typically found in partner selection problems in practice.     

一种新的不确定多目标规划问题求解方法研究

传统解决不确定多目标规划问题往往先将原问题转化为确定的多目标规划问题,再通过经典多目标规划方法进行求解,这种求解方法称之为多目标方法(Multiobjective approach).然而,采用多目标方法往往会忽略原问题的不确定性以及不确定目标之间的相关性,基于此,本文提出一种新的求解方法——不确定方法(Uncertain approach),通过不确定变量的序关系定义不确定多目标规划问题(UMOP问题)的Pareto有效解,将原问题转化为不确定单目标规划问题进行求解,为求解这类问题带来一种新的思路.     

一种新的不确定多目标规划问题求解方法研究

传统解决不确定多目标规划问题往往先将原问题转化为确定的多目标规划问题,再通过经典多目标规划方法进行求解,这种求解方法称之为多目标方法(Multiobjective approach).然而,采用多目标方法往往会忽略原问题的不确定性以及不确定目标之间的相关性,基于此,本文提出一种新的求解方法——不确定方法(Uncertain approach),通过不确定变量的序关系定义不确定多目标规划问题(UMOP问题)的Pareto有效解,将原问题转化为不确定单目标规划问题进行求解,为求解这类问题带来一种新的思路.     

New models for exhaustible resource development

Minerals sector firms have joined other industries in going green, and some have used the language of sustainable development in the context of the relationship between industry, environment and community. Because of its historical practices of causing severe land disturbance, water pollution and ecosystem disruption, many have thought the concept of ‘sustainable mining’ an oxymoron. Within the context of trying to find the ‘best’ models for minerals development in the fledgling Russian democracy (specifically in Western Siberia), however, we discovered a number of possibilities for creating at least a more sustainable mining sector. This paper presents in summary form some interim results from our work on sustainable development in the extractive hydrocarbon economies of Western Siberia. We identify practices along three dimensions of sustainability – environment, community and labor – and briefly discuss the implications of these practices for Western Siberia.     

Breaking ties in collective decision-making

Decisions in Economics and Finance - Many classic social preference (multiwinner social choice) correspondences are resolute only when two alternatives and an odd number of individuals are...     

The approximate solution of finite‐horizon discrete‐choice dynamic programming models

The estimation of finite‐horizon discrete‐choice dynamic programming (DCDP) models is computationally expensive. This limits their realism and impedes verification and validation efforts. Keane and Wolpin (Review of Economics and Statistics, 1994, 76(4), 648–672) propose an interpolation method that ameliorates the computational burden but introduces approximation error. I describe their approach in detail, successfully recompute their original quality diagnostics, and provide some additional insights that underscore the trade‐off between computation time and the accuracy of estimation results.     

Methods for analyzing decision-making: a framework approach

In political science an eternal question concerns how decisions and policies arise. Modern society, characterized by more uncertainty and complexity than before, increases the challenge of providing valid answers. However, the general lack of methodological concern in several previous studies in this area stresses the need for elaborations of more suitable approaches. In this article we add a methodological perspective that deals with this very question. By reviewing and analyzing earlier research on how decision-making is reached, the overall ambition of this article is to create a framework that can lay the methodological foundation for further studies. Such a framework, which takes into account both the complexity of modern multi-governance societies and adds methodological perspectives of macro and micro standpoints as well as of causal mechanisms, can be used in future research to achieve richer pictures of how decision-making is carried out. In addition, we show how a certain technique of analysis is highly compatible to this framework and that jointly these features provide solutions for a better understanding of the complexity of modern decision-making. All in all, applying this strategy can be used to better systematize complex causal chains that reflect different analytical levels and thereby increase leverage on how to understand and explain the process of political decisions.     

Group decision-making: Head-count versus intensity of preference

This paper puts forth a framework for reshaping the group decision-making process. The proposed framework extends from the usual one-issue-at-a-time decision-making to one that involves several related issues simultaneously. Weaknesses of the traditional majority voting mechanism are first identified, and then a different voting method that takes each individual voter's sentiment into account is discussed. Specifically, a decision-maker is asked to express his/her intensity of preference for the issues encountered. Three hierarchical structures—benefits, costs, and risks—are developed to evaluate the alternatives. Due to the nature of pairwise comparisons and synthesis, the proposed method is amenable to consensus building and has higher reliability and consistency. It can be used for candidate selection, e.g. governmental election, when a large population is involved. It is also effective for resource allocation and prioritization when a small group or business is concerned. We believe the proposed approach has potential for resolving deficiencies of the conventional voting mechanism, and can be applied to many real-world problems. Its implementation on the Internet is also discussed.