In [5] an evolutionary algorithm for detecting continuous Pareto optimal sets has been proposed. In this paper we propose a new evolutionary elitist approach combing a non-standard solution representation and an evolutionary optimization technique. The proposed method permits detection of continuous decision regions. In our approach an individual (a solution) is either a closed interval or a po...

Multi-objective optimization (MO) is a highly demanding research topic because many realworld optimization problems consist of contradictory criteria or objectives. Considering these competing objectives concurrently, a multi-objective optimization problem (MOP) can be formulated as finding the best possible solutions that satisfy these objectives under different tradeoff situations. A family o...

This work studies the behavior of three elitist multiand many-objective evolutionary algorithms generating a high-resolution approximation of the Pareto optimal set. Several search-assessment indicators are defined to trace the dynamics of survival selection and measure the ability to simultaneously keep optimal solutions and discover new ones under different population sizes, set as a fraction...

In this paper, the uncertain transition matrices for inhomogeneous Markov decision processes are described by use of fuzzy sets. Introducing a ν-step contractive property, called a minorization condition, for the average case, we fined a Pareto optimal policy maximizing the average expected fuzzy rewards under some partial order. The Pareto optimal policies are characterized by maximal solution...

In this paper, a Markov decision model with uncertain transition matrices, which allow a matrix to fluctuate at each step in time, is described by the use of fuzzy sets. We find a pareto optimal policy maximizing the infinite horizon fuzzy expected discounted reward over all stationary policies under some partial order. The pareto optimal policies are characterized by maximal solutions of an op...

Conflict resolution, e.g. negotiation, is frequently about an interactive process that forces agents to make concessions in order to resolve the conflict. In multilateral negotiations, concessions might be directed to one or another partner. In isolated negotiations such directed concessions might be less useful, but may become important for interdependent negotiations. We present weight-based ...

This paper addresses a multi-objective order scheduling problem in production planning under a complicated production environment with the consideration of multiple plants, multiple production departments and multiple production processes. A Pareto optimization model, combining a NSGA-II-based optimization process with an effective production process simulator, is developed to handle this probl...

The trade-off between obtaining a wellconverged and well-distributed set of Pareto optimal solutions, and obtaining them efficiently and automatically is an important issue in multi-objective evolutionary algorithms (MOEAs). Many studies have depicted different approaches that evolutionary algorithms can progress towards the Pareto optimal set with a wide-spread distribution of solutions. Howev...

The extant supply chain management literature has not addressed the issue of coordination in supply chains involving risk-averse agents. We take up this issue and begin with defining a coordinating contract as one that results in a Pareto-optimal solution acceptable to each agent. Our definition generalizes the standard one in the risk-neutral case. We then develop coordinating contracts in thr...

Service composition is popular for composing a set of existing services to provide complex services. With the increasing number of services deployed in cloud computing environments, many service providers have started to offer candidate services with equivalent functionality but different Quality of Service (QoS) levels. Therefore, QoS-aware service composition has drawn extensive attention. Mo...