A survey of current continuous nonlinear multi-objective optimization (MOO) concepts and methods is presented. It consolidates and relates seemingly different terminology and methods. The methods are divided into three major categories: methods with a priori articulation of preferences, methods with a posteriori articulation of preferences, and methods with no articulation of preferences. Genetic algorithms are surveyed as well. Commentary is provided on three fronts, concerning the advantages and pitfalls of individual methods, the different classes of methods, and the field of MOO as a whole. The Characteristics of the most significant methods are summarized. Conclusions are drawn that reflect often-neglected ideas and applicability to engineering problems. It is found that no single approach is superior. Rather, the selection of a specific method depends on the type of information that is provided in the problem, the user’s preferences, the solution requirements, and the availability of software.

Survey of multi-objective optimization methods for engineering

Multi-Criteria Decision Making (MCDM) techniques are gaining popularity in sustainable energy management. The techniques provide solutions to the problems involving conflicting and multiple objectives. Several methods based on weighted averages, priority setting, outranking, fuzzy principles and their combinations are employed for energy planning decisions. A review of more than 90 published papers is presented here to analyze the applicability of various methods discussed. A classification on application areas and the year of application is presented to highlight the trends. It is observed that Analytical Hierarchy Process is the most popular technique followed by outranking techniques PROMETHEE and ELECTRE. Validation of results with multiple methods, development of interactive decision support systems and application of fuzzy methods to tackle uncertainties in the data is observed in the published literature.

/pdf/application-of-multi-criteria-decision-making-to-sustainable-2thqepybyg.pdf

Application of multi-criteria decision making to sustainable energy planning—A review

Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems

In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

A typology of cutting and packing problems

Multiple objective decision making - methods and applications: A state-of-the art survey: Ching-Lai HWANG and Abu Syed Md. MASUD Springer, Berlin, 1979, xii + 351 pages, Dfl. 46.90. Soft cover

Because of the diversity of the structures of real-world trim loss (or cutting stock) problems there exist no general standard methods for solving these problems. Hence many solution methods for trim loss problems have been developed in practice, especially heuristics. Since these methods are strongly based on the particular problems to which they are applied, the study of papers on problems with a comparable structure may prove helpful. In this paper a detailed catalogue of criteria for characterization of real-world trim loss problems is developed in a differentiated and systematic manner. The main criteria are: dimension, planning situation, goal, restrictions and solution approach. The proposed system of classification is based on 34 case studies found in the relevant literature. The classification of these case studies is represented by means of a ‘classification schedule’. In view of existing formal similarities the classification system can also be of importance for (bin) packing and loading as well as some assortment problems.

Trim loss and related problems

The logistics distribution problem is to allocate a number of points of consumption to a number of points of supply, including suppliers, manufacturers, warehouses, distribution centers, and customers. The connection of these various logistics stakeholders by a mean of transportation facilities is regarded as the logistics distribution network. Logistics distribution network design is one of the major decision problems arising in contemporary supply chain management. There are mainly two inadequacies in the traditional approaches for the problem. First, the focus was confined to the points of supply only. The objective was either to minimize the total logistics cost or total delivery time. However, the viewpoints of customers were neglected. Second, only quantifiable data were considered in the optimization techniques. Some qualitative factors, which are mainly customer oriented, were not considered.

Multiple Criteria Decision Making

On Efficient Sets in Vector Maximum Problems — A Brief Survey

Redistribution of funds for teaching and research among universities: The case of North Rhine-Westphalia

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