Requirements prioritisation is a key decision making activity of the software development process, which relies on the capability of different decision-makers to identify the optimal candidate rankings of the requirements, in order to be able to perform a strategic choice among them. In this paper, we formulate such multi-decision-maker requirements prioritisation as a multi-objective optimisat...

<p style='text-indent:20px;'>In this paper, we study the single-machine Pareto-scheduling of jobs with multiple weighting vectors for minimizing total weighted late works. Each vector has its corresponding work. The goal problem is to find Pareto-frontier works vectors. When number arbitrary, it implied in literature that unary NP-hard. Then concentrate on our research under assumption a ...

A stationary variant of the repeated prisoners’ dilemma in which the game frontier is a parallelogram is analyzed. By using the probabilistic cheap talk concept of [3], the discount factor becomes fungible, and for a critical value of the discount factor a unique Pareto-optimal and Pareto-dominant solution can be found. The relative bargaining power of the players can be quantified in terms of ...

Recent years of empirical research have collected enough evidences that for efficient markets the process of lower-wealth accumulation by capital investment is approximated by log-normal and high-wealth range by Pareto wealth distribution. This research aims to construct a simple neural network (NN) based multiagent system of heterogeneous agents’ targeted to get on the efficiency frontier by c...

Normally distributed data arises in various contexts and often one is interested in estimating its variance. The authors limit themselves in this chapter to the class of estimators that are (positive) multiples of sample variances. Two important qualities of estimators are bias and variance, which respectively capture the estimator’s accuracy and precision. Apart from the two classical estimato...

We study a bi-objective covering problem stemming from real-world application concerning the design of camera surveillance systems for large-scale outdoor areas. It is in this prohibitively costly to surveil entire area, and therefore necessary be able present decision-maker with trade-offs between total cost portion area that surveilled. The can stated as set two objectives, describing constra...

In this work, authors discuss the way of selecting level supplier by using concept binary coded genetic algorithm. For best solution due to involvement multi objective functions, process Tournament selection is widely discussed. addition this, involve fuzzy parameters aspiration levels Decision maker in analysis part for more clarity towards optimality. As a case study pareto optimality, theory...

Simple and complex contracts Negotiation protocols work, in general, via the iterative exchange of proposals and counter-proposals. An agent starts with a contract that’s optimal for that agent and makes concessions, in each subsequent proposal, until either an agreement is reached or the negotiation is abandoned because the latest proposal’s utility has fallen below the agents’ reservation val...

A multi-objective chance-constrained programming integrated with Genetic Algorithm and robustness evaluation methods was proposed to weigh the conflict between system investment against risk for watershed load reduction, which was firstly applied to nutrient load reduction in the Lake Qilu watershed of the Yunnan Plateau, China. Eight sets of Pareto solutions were acceptable for both system inv...