João Luís de Miranda

A Case of Cooperation in the European OR Education.

European cooperation is a relevant subject that contributes to building a competitive network of high education institutions. A case of teacher mobility on behalf of the Erasmus programme is presented: it considers some Operations Research topics and the development of the Lego on My Decision module. The module considers eight lecture hours in four sessions: (i) the introductory session, to focus on the basics of computational linear algebra, linear programming, integer programming, with computational support (Excel®); (ii) the interim session, to address modelling subjects in a drop by-session; (iii) the advanced session, on the sequence of (i), to consider uncertainty and also how to use multi-criteria decision-making methods; (iv) the final session, to perform the evaluation of learning outcomes. This cooperation at European level is further exploited, including curricula normalisation and adjustments, cultural exchanges and research lines sharing in the idea of promoting the mobility of students and faculty.

OR/MS Education in a Changing Environment

The world is changing fast on various fronts and at accelerating speeds. Technological innovations and developments are happening so fast that it is impossible to keep track of all the new inventions, changes, etc. In addition globalization is also creating closer connectivity between many countries and nations. A third force namely climate change is a reality and the effects of that can be felt across the globe. It is within this fast changing world and market place that OR/MS professionals need to operate. Many of these changes will disrupt traditional models and approaches to solving problems. New ways will need to be developed. This makes it essential that OR/MS courses at educational institutions are continuously revised, upgraded and changed to enable the OR/MS students to meet the challenges within this fast changing world. This chapter gives a brief perspective of some of the main developments as well as changes that directly impact OR/MS. An attempt is made to show what the future skills requirements will be for OR/MS students.

European Study on OR/MS Education

Many studies have been done regarding the higher education international context in general, however none of these studies specifically focussed on the way that Operations Research/Management Science (OR/MS) education is perceived at European level as well as the related key factors.

OR/MS Education: Good Practices and International Cooperation

In this work, an overview of good practices in OR/MS Education and of European projects is presented. Beyond the talks on OR/MS education presented in two of the most relevant international OR/MS conference series (EURO and IFORS), the talks on Portuguese OR/MS conference series, also the projects developed on behalf of the Education, Audiovisual and Culture Executive Agency (EACEA) are addressed here. The purposes are to reinforce the insight of the main trends on OR/MS education in order to further contribute to a deeper knowledge on the OR/MS education subject. The main characteristics of the good practices and international cooperation in OR/MS education are addressed; for one side, classroom approaches, courses design, courses assessment; and for other side the applications of OR/MS tools on Education, such as Data Envelopment Analysis (DEA), Modeling/Simulation, Scheduling/Timetabling, Decision Support Systems (DSS), Routing for school transportation, Data Mining, Multicriteria Decision Analysis (MCDA), Data Analysis, Metaheuristics, Graph Theory/Combinatorial Optimization and Statistics, among others. The impact of such practices, so as its extension, in some important topics for the effectiveness and performance of higher education institutions (HEI) is also aimed.

Optimization Concepts: II—A More Advanced Level

Optimization subjects are addressed from both an introductory and an advanced standpoint. Theoretical subjects and practical issues are focused, conjugating Optimization basics with the implementation of useful tools and supply chain (SC) models. In the prior Introductory chapter on Optimization concepts, Linear Programming, Integer Programming, related models, and other basic notions were treated. Here, the More Advanced chapter is directed to Robust Optimization, complex scheduling and planning applications, thus the reading of the prior Introductory chapter is recommended. Through a generalization approach, scheduling and planning models are enlarged from deterministic to stochastic frameworks and robustness is promoted: model robustness, by reducing the statistical measures of solutions variability; and solutions robustness, by reducing the capacity slackness, the non-used capacity of chemical processes that would imply larger investment costs.

Optimization Concepts—I: Introductory Level

Optimization subjects are addressed from both an introductory and an advanced standpoint. Theoretical subjects and practical issues are focused, conjugating Optimization basics with the implementation of useful tools and SC (supply chain) models. By now, in the Introductory section, Linear Programming, Integer Programming, related models, and others of interest are treated. In another chapter about these subjects in this handbook, more advanced related topics are addressed.

An Introduction to the Resource Constrained Project Scheduling Problem Solving Techniques

A project can be defined as a set of activities. Each activity needs a certain amount of time (that can be variable or even stochastic) and requires different type and quantity of resources (tools, personnel, money, etc.). Also, usually there are additional constraints that affect the scheduling of the activities, such as precedence constraints (for example, an activity cannot start until another one has finished), time constraints (do not start or finish before or later than a certain date) and simultaneously constraints (activities that cannot be done at the same time). In this chapter, different tools for project scheduling will be introduced: graph representation of time and precedence constraints; Gantt chart and load curves; and heuristic and exact algorithms for project scheduling considering different evaluation criteria. Then, a simple case of project scheduling is presented and solved using the described tools, allowing useful comparison between the graph-based approaches and the exact approach of a Mixed Integer Linear Programming (MILP) model implemented in IBM ILOG CPLEX. The implementation and verification procedure followed here allows the enlargement of project applications beyond commercial applications or open literature.

Operations Research and Big Data

Sectorization means dividing a whole into parts (sectors), a procedure that occurs in many contexts and applications, usually to achieve some goal or to facilitate an activity. The objective may be a better organization or simplification of a large problem into smaller sub-problems. Examples of applications are political districting and sales territory division. When designing/comparing sectors some characteristics such as contiguity, equilibrium and compactness are usually considered. This paper presents and describes new generic measures and proposes a new measure, desirability, connected with the idea of preference.