Abstract
Given an edge-weighted graph, the maximum edge weight clique (MEWC) problem is to find a clique that maximizes the sum of edge weights within the corresponding complete subgraph. This problem generalizes the classical maximum clique problem and finds many real-world applications in molecular biology, broadband network design, pattern recognition and robotics, information retrieval, marketing, and bioinformatics among other areas. The main goal of this chapter is to provide an up-to-date review of mathematical optimization formulations and solution approaches for the MEWC problem. Information on standard benchmark instances and state-of-the-art computational results is also included. © Springer International Publishing AG 2017.

Abstract
Genetic algorithms and other evolutionary algorithms have been successfully applied to solve constrained minimum spanning tree problems in a variety of communication network design problems. In this paper, we enlarge the application of these types of algorithms by presenting a multi-population hybrid genetic algorithm to another communication design problem. This new problem is modeled through a hop-constrained minimum spanning tree also exhibiting the characteristic of flows. All nodes, except for the root node, have a nonnegative flow requirement. In addition to the fixed charge costs, nonlinear flow dependent costs are also considered. This problem is an extension of the well know NP-hard hop-constrained Minimum Spanning Tree problem and we have termed it hop-constrained minimum cost flow spanning tree problem. The efficiency and effectiveness of the proposed method can be seen from the computational results reported.

Abstract
Nowadays, organizations are often faced with the development of complex and innovative projects. This type of projects often involves performing tasks which are subject to failure. Thus, in many such projects several possible alternative actions are considered and performed simultaneously. Each alternative is characterized by cost, duration, and probability of technical success. The cost of each alternative is paid at the beginning of the alternative and the project payoff is obtained whenever an alternative has been completed successfully. For this problem one wishes to find the optimal schedule, i.e., the starting time of each alternative, such that the expected net present value is maximized. This problem has been recently proposed in Ranjbar (Int Trans Oper Res 20(2):251-266, 2013), where a branch-and-bound approach is reported. Since the problem is NP-Hard, here we propose to solve the problem using genetic algorithms.

Abstract
Hop constraints are used to limit the number of links between two given points in a network, this way improving the quality of service by increasing the availability and reliability of the network. They have been applied to a limited number of problems, although their application can be of the greatest importance both from the academical and practical points-of-view. In this work, we survey relevant and recent works on hop-constrained problems focusing on problems with free shaped solutions.

Abstract
The painting activity is one of the most complex and important activities in automobile manufacturing. The inherent complexity of the painting activity and the frequent need for repainting usually turn the painting process into a bottleneck in automobile assembly plants, which is reflected in higher operating costs and longer overall cycle times. One possible approach for optimizing the performance of the paint shop is to improve the efficiency of the color planning. This can be accomplished by evaluating the relative merits of a set of vehicle painting plans. Since this problem has a multicriteria nature, we resort to the multicriteria decision analysis (MCDA) methodology to tackle it. A recent trend in the MCDA field is the development of hybrid approaches that are used to achieve operational synergies between different methods. Here we apply, for the first time, an integrated approach that combines the strengths of the analytic hierarchy process (AHP) and the Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), aided by Geometrical Analysis for Interactive Aid (GAIA), to the problem of assessing alternative vehicle painting plans. The management of the assembly plant found the results of value and is currently using them in order to schedule the painting activities such that an enhancement of the operational efficiency of the paint shop is obtained. This efficiency gain has allowed the management to bid for a new automobile model to be assembled at this specific plant.

Abstract
Performance appraisal increasingly assumes a more important role in any organizational environment. In the trucking industry, drivers are the company's image and for this reason it is important to develop and increase their performance and commitment to the company's goals. This paper aims to create a performance appraisal model for trucking drivers, based on a multi-criteria decision aid methodology. The PROMETHEE and MMASSI methodologies were adapted using the criteria used for performance appraisal by the trucking company studied. The appraisal involved all the truck drivers, their supervisors and the company's Managing Director. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used. The results are to be used as a decision-making tool to allocate drivers to the domestic haul service.