In any manufacturing system, the cost is considered to be the most significant factor and the reliability of any industrial system is also an increasingly important issue. On the other hand the available information about the constituent components of the system is most of the time imprecise, incomplete, vague and conflicting and the management decisions are based on experience. So it is very d...

Almost every real world problem involves simultaneous optimization of several incommensurable and often competing objectives which constitutes a multi-objective optimization problem. In multi-objective optimization problems the optimal solution is not unique as in single-objective optimization problems. This paper is concerned with large-scale structural optimization of skeletal structures such...

A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective functi...

The hub location problem is employed for many real applications, including delivery, airline and telecommunication systems and so on. This work investigates on hierarchical hub network in which a three-level network is developed. The central hubs are considered at the first level, at the second level, hubs are assumed which are allocated to central hubs and the remaining nodes are at the third ...

A number of the practical scenarios relating to sensor networks are modeled as multiobjective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to choose one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/outp...

In this paper, we propose a new multi-objective contextual multi-armed bandit (MAB) problem with two objectives, where one of the objectives dominates the other objective. Unlike single-objective MAB problems in which the learner obtains a random scalar reward for each arm it selects, in the proposed problem, the learner obtains a random reward vector, where each component of the reward vector ...

this paper will investigate the optimum portfolio for an investor, taking into account 5 criteria. the mean variance model of portfolio optimization that was introduced by markowitz includes two objective functions; these two criteria, risk and return do not encompass all of the information about investment; information like annual dividends, s&p star ranking and return in later years which...

In this paper, we examine the application of Multi-Agent Reinforcement Learning (MARL) to a Dynamic Economic Emissions Dispatch problem. This is a multi-objective problem domain, where the conflicting objectives of fuel cost and emissions must be minimised. We evaluate the performance of several different MARL credit assignment structures in this domain, and our experimental results show that M...

Human resource is a key factor for IT new product development. Considering multi-skilled employees in IT Project Portfolio Scheduling, a mixed integer nonlinear programming model with three optimization objectives is proposed from the view of project or product managers. The three objectives are to maximize the increments of skill efficiency values for all multi-skilled employees, to minimize R...

Unpublished AIChE will not be responsible for statements or opinions contained in papers or printed in its publications 1 Abstract The design and optimization of fuel cells in hybrid power systems is a complex problem involving integration of various components. At conceptual level, fuel cell power system consists of four components: (1) fuel processor, (2) fuel Power system, (3) power conditio...