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This paper updates the literature regarding the performance of constrained US mutual funds by looking at the relative performance of Christian mutual funds, socially responsible funds and Islamic funds. This paper aims to rank the performance of religious and ethical investment funds.

This study uses monthly returns from 2005 to 2015 to perform traditional asset pricing models as well as data envelopment analysis to determine rank.

Islamic mutual funds outperform socially responsible funds, which then outperform Christian-based mutual funds; these results are also consistent during the latest 2007-2008 crisis period. The results are robust to different performance metrics and benchmarks. Moreover, this paper reports a significant amount of money “left on the table” by investing in constraint funds and disregarding the sin industry which shows an ethical dilemma for investors.

Investors who seek to invest morally/ethically can be informed of the cost of doing so. They can also compare portfolio with others that have similar holdings and constraints.

This paper not only includes Christian mutual funds in the research but also provides the performance of all constrained assets. It also compares religious funds with “SIN” industry, and thus quantifies the cost of “doing right.”

The purpose is to create an algorithm that optimizes the trajectories that an autonomous vehicle must follow to reduce its energy consumption and reduce the emission of greenhouse gases.

An algorithm is presented that respects the dynamic constraints of the robot, including the characteristics of power delivery by the motor, the behaviour of the tires and the basic inertial parameters. Using quadratic sequential programming with distributed and non-monotonous search direction (Quadratic Programming Algorithm with Distributed and Non-Monotone Line Search), an optimization algorithm proposed and developed by Professor K. Schittkowski is implemented.

Relations between important operating variables have been obtained, such as the evolution of the autonomous vehicle’s velocity, the driving torque supplied by the engine and the forces acting on the tires. In a subsequent analysis, the aim is to analyse the relationship between trajectory made and energy consumed and calculate the reduction of greenhouse gas emissions. Also this method has been checked against another different methodology commented on in the references.

The main limitation comes from the modelling that has been done. As greater is the mechanical systems analysed, more simplifying hypotheses should be introduced to solve the corresponding equations with the current computers. However, the solutions are obtained and they can be used qualitatively to draw conclusions.

One main objective is to obtain guidelines to reduce greenhouse gas emissions by reducing energy consumption in the realization of autonomous vehicles’ trajectories. The first step to achieve that is to obtain a good model of the autonomous vehicle that takes into account not only its kinematics but also its dynamic properties, and to propose an optimization process that allows to minimize the energy consumed. In this paper, important relationships between work variables have been obtained.

The idea is to be friendly with nature and the environment. This algorithm can help by reducing an instance of greenhouse gases.

Originality comes from the fact that we not only look for the autonomous vehicle’s modelling, the simulation of its motion and the analysis of its working parameters, but also try to obtain from its working those guidelines that are useful to reduce the energy consumed and the contamination capability of these autonomous vehicles or car-like robots.

This paper aims to expand the literature on financial and operational performance by analyzing the effects of undergoing through Six Sigma training.

The effects of implementing Six Sigma trainings is analyzed for 108 Fortune 500 companies. The authors estimate long-term stock returns and 14 financial ratios of Six Sigma companies, both pre- and post-adoption periods. Furthermore, The authors match the 108 companies by size and industry to 108 non-Six Sigma companies also within the Fortune 500.

Looking at long-term stock returns, the evidence shows that Six Sigma firms need at least four years before they start to outperform the controlling sample. Furthermore, looking at operational performance, unlike prior reported results, the authors find supporting, and more importantly, persisting statistical evidence that Six Sigma firms are less liquid and have a negative growth in staff levels in comparison to the matching firms.

The findings of this suggest that if Six Sigma provides any value to the company, it comes at the expense of overloaded staff levels, as evidenced by the fact that Six Sigma firms have less growth in staff levels than the matching firms.

It is one of the first paper to thoroughly investigate the effects on both financial performance and operational performance of spending, sometimes billions of dollars, in Six Sigma training.

This paper analyses Roman fish tanks, which have functional elements that could be used to research on palaeo-sea-levels. Thus, the conditions of 37 installations in the Western Mediterranean basin are reviewed to identify those that have the best environmental and constructive conditions to be analyzed.

The methodology was largely based on the review of existing scientific bibliography dealing with sea-level variations from studies on historical constructions, existing historical documentation on Roman fish tanks on the Mediterranean coast, as well as the fieldwork carried out in fish tanks on the Mediterranean coasts.

The Roman coastal fish tanks located in the shoreline of the Western Mediterranean Sea have turned out to be an excellent indicator of sea-level changes. Nevertheless, current coastal retreat, erosion and storm surges are posing significant threats to their preservation, and they could be considered as a heritage at risk of disappearance. Moreover, variations in the tectonic behaviour of the different coastal sectors make it challenging to select these facilities as an indicator of the sea level.

The analysis of Late Holocene sea-level changes and palaeoenvironments from archaeological and biological evidences, although not without difficulties, is very convenient because it provides very precise data that cannot be obtained with other absolute dating methods. This approach is increasingly gaining popularity with researchers and is very innovative in its method of combining the results of several scientific disciplines.

The purpose of this paper is to compare the quality and efficiency of five methods for solving the path planning problem of industrial robots in complex environments.

In total, five methods are presented for solving the path planning problem and certain working parameters have been monitored using each method. These working parameters are the distance travelled by the robot and the computational time needed to find a solution. A comparison of results has been analyzed.

After this study, it could be easy to know which of the proposed methods is most suitable for application in each case, depending on the parameter the user wants to optimize. The findings have been summarized in the conclusion section.

The five techniques which have been developed yield good results in general.

The algorithms introduced are able to solve the path planning problem for any industrial robot working with obstacles.

The path planning algorithms help robots perform their tasks in a more efficient way because the path followed has been optimized and therefore they help human beings work together with the robots in order to obtain the best results from them.

The paper shows which algorithm offers the best results, depending on the example the user has to solve and the parameter to be optimized.

The purpose of this paper is to solve the trajectory planning problem of industrial robots in a complex environment.

A simultaneous algorithm was presented in which the trajectory was generated gradually as the robot moves. It takes into account the presence of obstacles (to avoid collisions) and differential constraints related to the dynamics of the robotic system. The method poses an optimization problem that aims at minimizing the time to perform the trajectory when several interpolation functions are used.

A new approach to solving the trajectory planning problem in which the behaviour of four operational parameters (execution time, computational time, distance travelled and number of configurations) have been analyzed when changing the interpolation functions, therefore enabling the user to choose the most efficient algorithm depending on which parameter the user is most interested in. From the examples solved the interpolation function that yields the best results has been found.

This new technique is very time consuming due to the great number of mathematical calculations that have to be made. However, it yields a solution.

The algorithm is able to obtain the solution to the trajectory planning problem for any industrial robot. Also, even mobile obstacles in the workspace could be incorporated at the same time as the robot is moving and creating the path and the time history of motion.

It gives a new tool for solving the trajectory planning problem and describes the best interpolation function.

The purpose of this paper is to analyze the impact of the torque, power, jerk and energy consumed constraints on the generation of minimum time collision‐free trajectories for industrial robots in a complex environment.

An algorithm is presented in which the trajectory is generated under real working constraints (specifically torque, power, jerk and energy consumed). It also takes into account the presence of obstacles (to avoid collisions) and the dynamics of the robotic system. The method solves an optimization problem to find the minimum time trajectory to perform the tasks the robot should do.

Important conclusions have been reached when solving the trajectory planning problem related to the value of the torque, power, jerk and energy consumed and the relationship between them, therefore enabling the user to choose the most efficient way of working depending on which parameter he is most interested in optimizing. From the examples solved the authors have found the relationship between the maximum and minimum values of the parameters studied.

This new approach tries to model the real behaviour of the actuators in order to be able to upgrade the trajectory quality, so a lot of work has to be done in this field.

The algorithm solves the trajectory planning problem for any industrial robot and the real characteristics of the actuators are taken into account, which is essential to improve the performance of it.

This new tool enables the performance of the robot to be improved by combining adequately the values of the mentioned parameters (torque, power, jerk and consumed energy).

The purpose of this paper is to solve the path‐planning problem of industrial robots in complex environments.

A direct method (in each step, the path is been recorded) is presented in which the search of the path is made in the state space of the robotic system, and it makes use of the information generated about the characteristics of the process, introducing graph techniques for branching. The method poses an optimization problem that aims at minimizing the distance travelled by the significant points of the robot.

A new approach to solve the path‐planning problem has been introduced in which the behaviour of three operational parameters (computational time, distance travelled and number of configurations generated) have been analyzed so that the user can choose the most efficient algorithm depending on which parameter he is most interested in.

A new technique has been introduced which yields good results as the examples show.

The algorithm is able to obtain the solution to the path‐planning problem for any industrial robot working in a complex environment.

Gives a new tool for solving the path‐planning problem.

The purpose of this paper is to study whether Islamic investors lose portfolio efficiency due to a limited asset universe.

The paper contributes to prior literature by using non‐parametrical measurements of efficiency instead of regular (parametrical) methods. Data envelopment analysis (DEA) was used in order to better characterize the risk and return relationship, as well as estimating a single performance index to rank different funds and compare them to one another.

Overall, the results are congruent with prior findings. That is, there is strong evidence suggesting that Islamic funds are highly efficient and that they outperform their international counterparts. Also, results are robust to different estimation of DEA, the specification of the asset universe, and the inclusion of financial crisis period in analysis.

Though the paper's findings are robust to different specifications of the DEA model and time periods, the authors caution readers due to the limited sample.

Having defined a performance index, one can therefore isolate the funds which are the most efficient and thus drive trading activities towards said funds.

Since the paper's findings suggest that Islamic investors do not lose efficiency, investing into a limited asset universe which follows social and ethical constraints (given by Shariah law) is recommended.

The paper is able to confirm prior literature, even by using a non‐parametrical measurement of efficiency. In this way, the authors have accounted for an extra penalty on the risk‐return relationship: skewness.