Trinidad Gómez

Solving a comprehensive model for multiobjective project portfolio selection

Any organization is routinely faced with the need to make decisions regarding the selection and scheduling of project portfolios from a set of candidate projects. We propose a multiobjective binary programming model that facilitates both obtaining efficient portfolios in line with the set of objectives pursued by the organization, as well as their scheduling regarding the optimum time to launch each project within the portfolio without the need for a priori information on the decision-makers preferences. Resource constraints, the possibility of transferring resources not consumed in a given a period to the following one, and project interdependence have also been taken into account. Given that the complexity of this problem increases as the number of projects and the number of objectives increase, we solve it using a metaheuristic procedure based on Scatter Search that we call SS-PPS (Scatter Search for Project Portfolio Selection). The characteristics and effectiveness of this method are compared with other heuristic approaches (SPEA and a fully random procedure) using computational experiments on randomly generated instances. Statement of scope and purpose: This paper describes a model to aid in the selection and scheduling of project portfolios within an organization. The model was designed assuming strong interdependence between projects, which therefore have to be assessed in groups, while allowing individual projects to start at different times depending on resource availability or any other strategic or political requirements, which involves timing issues. The simultaneous combination of project portfolio selection and scheduling under general conditions involves known drawbacks that we attempt to remedy. Finally, the model takes into account multiple objectives without requiring a priori specifications regarding the decision-makers preferences. The resolution of the problem was approached using a metaheuristic procedure, which showed by computational experiments good performance compared with other heuristics.

Assessing the sustainability of small wastewater treatment systems: A composite indicator approach

The assessment of the sustainability of wastewater treatment (WWT) systems has gained interest in recent years. However, most previous studies have focused on environmental and/or economic dimensions ignoring social aspects. Moreover, they tend to be based on sets of indicators rather than providing a holistic assessment. To overcome this limitation, this paper proposes an innovative methodology to assess the sustainability of WWT systems based on the development of a composite indicator embracing economic, environmental and social issues. Subsequently, the global sustainability of seven WWT technologies for secondary treatment in small communities is compared. The joint application of the analytical hierarchical process (AHP) to assign weights to each indicator allows the incorporation of the preferences of experts. Initially, the global sustainability of the WWT technologies evaluated is quite similar. However, a scenario analysis illustrates that constructed wetlands technology is the most sustainable in five out of the seven scenarios evaluated. Moreover, extended aeration and rotating biological contactors are identified as the technologies with the lowest variability in their sustainability. Hence, in an uncertain context, they might be considered the preferred options. The proposed approach contributes to ease of interpretation of a complex problem such as the selection of the most sustainable WWT alternative.

Solving a bi-objective Transportation Location Routing Problem by metaheuristic algorithms

In this work we consider a Transportation Location Routing Problem (TLRP) that can be seen as an extension of the two stage Location Routing Problem, in which the first stage corresponds to a transportation problem with truck capacity. Two objectives are considered in this research, reduction of distribution cost and balance of workloads for drivers in the routing stage. Here, we present a mathematical formulation for the bi-objective TLRP and propose a new representation for the TLRP based on priorities. This representation lets us manage the problem easily and reduces the computational effort, plus, it is suitable to be used with both local search based and evolutionary approaches. In order to demonstrate its efficiency, it was implemented in two metaheuristic solution algorithms based on the Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization (SSPMO) and on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) strategies. Computational experiments showed efficient results in solution quality and computing time.

Budgetary allocations and efficiency in the human resources policy of a university following multiple criteria

This study proposes a methodology to serve as a guiding mechanism for the allocation and management of university financial resources taking efficiency as its objective. Specifically, an aid model is provided for decision making, so that the planning of staff policy within a university guarantees an equal treatment of all the teaching and research units, greater transparency in the allocation of financial resources, as well as a rational monitoring of the allocations made and their effects on the university efficiency levels. The model we provide is based on the use of two quantitative techniques: data envelopment analysis (DEA) and multiple criteria decision making (MCDM), both techniques being linked in a way which makes it possible to transfer information from one to the other.

Assessment of wastewater treatment alternatives for small communities: An analytic network process approach

The selection of the most appropriate wastewater treatment (WWT) technology is a complex problem since many alternatives are available and many criteria are involved in the decision-making process. To deal with this challenge, the analytic network process (ANP) is applied for the first time to rank a set of seven WWT technology set-ups for secondary treatment in small communities. A major advantage of ANP is that it incorporates interdependent relationships between elements. Results illustrated that extensive technologies, constructed wetlands and pond systems are the most preferred alternatives by WWT experts. The sensitivity analysis performed verified that the ranking of WWT alternatives is very stable since constructed wetlands are almost always placed in the first position. This paper showed that ANP analysis is suitable to deal with complex decision-making problems, such as the selection of the most appropriate WWT system contributing to better understand the multiple interdependences among elements involved in the assessment.

Hierarchial generation of pareto optimal solutions in large-scale multiobjective systems

In this paper, the problem of the determination of Pareto optimal solutions for certain large-scale systems with multiple conflicting objectives is considered. As a consequence, a two-level hierarchical method is proposed, where the global problem is decomposed into smaller multiobjective problems (lower level) which are coordinated by an upper level that has to take into account the relative importance assigned to each subsystem. The scheme that has been developed is an iterative one, so that a continuous information exchange is carried out between both levels in order to obtain efficient solutions for the initial global problem. The practical implementation of the developed scheme allows us to prove its efficiency in terms of processing time.

Multiple objectives decomposition-coordination methods for hierarchical organizations

Abstract In this paper, the integration of goal programming models and hierarchical programming models is analyzed. The systems under study are assumed to consist of interconnected subsystems with multiple goals in each. Three possible cases regarding the number of decision makers will be considered: (1) one decision maker for the overall goals and one decision maker for each subsystem, (2) conflicting decision makers who are interested in their subsystems, and (3) just one decision maker for the overall system. Next, conditions are stated under which the problem of obtaining satisfying solutions for problems (1) and (3) can be reduced to the problem of obtaining satisfying solutions for the case (2). In order to determine such solutions, hierarchical techniques which exploit the structure of a decomposable system are analyzed. The empirical implementation of the two algorithms proposed shows their efficiency in terms of processing time.

Efficient assignment of financial resources within a university system. Study of the University of Malaga

Abstract The aim of this study is to demonstrate how a Goal Programming model can be a very useful instrument in the decision-making process in a university system, above all in the case of carrying out efficient resource allocation between the units of which the system is composed. Specifically, this study is centered on the 142 knowledge areas of the University of Malaga (UMA). These areas are the most suitable functional units for this study because the teaching aims and coordination of research carried out normally coincide within them.

Multiobjective project portfolio selection with fuzzy constraints

Decision makers usually have to face a budget and other type of constraints when they have to decide which projects are going to be undertaken (to satisfy their requirements and guarantee profitable growth). Our purpose is to assist them in the task of selecting project portfolios. We have approached this problem by proposing a general nonlinear binary multi-objective mathematical model, which takes into account all the most important factors mentioned in the literature related with Project Portfolio Selection and Scheduling. Due to the existence of uncertainty in different aspects involved in the aforementioned decision task, we have also incorporated into the model some fuzzy parameters, which allow us to represent information not fully known by the decision maker/s. The resulting problem is both fuzzy and multiobjective. The results are complemented with graphical tools, which show the usefulness of the proposed model to assist the decision maker/s.

Algebra of Efficient Sets for Multiobjective Complex Systems

Complex systems are modeled as collections of multiobjective programs representing interacting subsystems of the overall system. Since the calculation of efficient sets of these complex systems is challenging, it is desirable to decompose the overall system into component multiobjective programs, that are more easily solved and then construct the efficient set of the overall system. For some classes of complex systems, algebraic properties of set operations and relations are developed between the efficient set of the overall system and the efficient sets of subproblems. The properties indicate that multiple decomposition and coordination schemes, with varying assumptions regarding the system, may be applied to the same initial system.