scholarly journals Multi-Objective Cloud Manufacturing Service Selection and Scheduling with Different Objective Priorities

2019 ◽  
Vol 11 (17) ◽  
pp. 4767 ◽  
Author(s):  
He ◽  
Jia ◽  
Zong ◽  
Huang
Keyword(s):  
Optimal Solution ◽  
Service Selection ◽  
Cloud Manufacturing ◽  
Phase Method ◽  
Two Phase ◽  
The Sustainable Development ◽  
Preference Information ◽  
Multi Objective ◽  
New Information ◽  
Service Selection And Scheduling

In recent years, with the support of new information technology and national policies, cloud manufacturing (CMfg) has developed rapidly in China. About CMfg, scholars have conducted extensive and in-depth research, among which multi-objective service selection and scheduling (SSS) attracts increasing attention. Generally, the objectives of the SSS problem involve several aspects, such as time, cost, environment and quality. In order to select an optimal solution, the preference of a decision maker (DM) becomes key information. As one kind of typical preference information, objective priorities are less considered in current studies. So, in this paper, a multi-objective model is first constructed for the SSS with different objective priorities. Then, a two-phase method based on the order of priority satisfaction (TP-OPS) is designed to solve this problem. Finally, computational experiments are conducted for problems with different services and tasks/subtasks, as well as different preference information. The results show that the proposed TP-OPS method can achieve a balance between the maximum comprehensive satisfaction and satisfaction differences, which is conducive to the sustainable development of CMfg. In addition, the proposed method allows the preference information to be gradually clarified, which has the advantage of providing convenience to DM.

scholarly journals Multi-Objective Service Selection and Scheduling with Linguistic Preference in Cloud Manufacturing

2019 ◽  
Vol 11 (9) ◽  
pp. 2619 ◽  
Author(s):  
Wei He ◽  
Guozhu Jia ◽  
Hengshan Zong ◽  
Jili Kong
Keyword(s):  
Service Management ◽  
Service Selection ◽  
Cloud Manufacturing ◽  
Multiple Objectives ◽  
Second Phase ◽  
Time Cost ◽  
Two Phase ◽  
Preference Information ◽  
Multi Objective ◽  
Service Selection And Scheduling

Service management in cloud manufacturing (CMfg), especially the service selection and scheduling (SSS) problem has aroused general attention due to its broad industrial application prospects. Due to the diversity of CMfg services, SSS usually need to take into account multiple objectives in terms of time, cost, quality, and environment. As one of the keys to solving multi-objective problems, the preference information of decision maker (DM) is less considered in current research. In this paper, linguistic preference is considered, and a novel two-phase model based on a desirable satisfying degree is proposed for solving the multi-objective SSS problem with linguistic preference. In the first phase, the maximum comprehensive satisfying degree is calculated. In the second phase, the satisfying solution is obtained by repeatedly solving the model and interaction with DM. Compared with the traditional model, the two-phase is more effective, which is verified in the calculation experiment. The proposed method could offer useful insights which help DM balance multiple objectives with linguistic preference and promote sustainable development of CMfg.

scholarly journals Virtual interpolation of discrete multi-objective programming solutions with probabilistic operation

2011 ◽  
Vol 22 (4) ◽  
pp. 379-389
Author(s):  
Ricardo C. Silva ◽  
Edilson F. Arruda ◽  
Fabrício O. Ourique
Keyword(s):  
Probability Distributions ◽  
Phase Method ◽  
Second Phase ◽  
Pareto Optimal ◽  
Two Phase ◽  
Term Operation ◽  
Multi Objective ◽  
Multi Objective Programming ◽  
Objective Programming

This work presents a novel framework to address the long term operation of a class of multi-objective programming problems. The proposed approach considers a stochastic operation and evaluates the long term average operating costs/profits. To illustrate the approach, a two-phase method is proposed which solves a prescribed number of K mono-objective problems to identify a set of K points in the Pareto-optimal region. In the second phase, one searches for a set of non-dominated probability distributions that define the probability that the system operates at each point selected in the first phase, at any given operation period. Each probability distribution generates a vector of average long-term objectives and one solves for the Pareto-optimal set with respect to the average objectives. The proposed approach can generate virtual operating points with average objectives that need not have a feasible solution with an equal vector of objectives. A few numerical examples are presented to illustrate the proposed method.

Methodical Extensions for Decomposition of Matrix-Based Design Problems

2010 ◽  
Vol 132 (6) ◽  
Author(s):  
Simon Li
Keyword(s):  
Formal Analysis ◽  
Optimal Solution ◽  
Phase Method ◽  
Problem Decomposition ◽  
Relief Valve ◽  
Two Phase ◽  
Design Problems ◽  
System Decomposition ◽  
Computing Effort ◽  
Binary Information

The two-phase method is a matrix-based approach for system decomposition, in which a system is represented by a rectangular matrix to capture dependency relationships of two sets of system elements. While the two-phase method has its own advantages in problem decomposition, this paper focuses on two methodical extensions to improve the method’s capability. The first extension is termed nonbinary dependency analysis, which can handle nonbinary dependency information, in addition to just binary information, of the model. This extension is based on the formal analysis of a resemblance coefficient to quantify the couplings among the model’s elements. The second extension is termed heuristic partitioning analysis, which allows the method to search for a reasonably good decomposition solution with less computing effort. This extension can be viewed as an alternative to the original partitioning approach that uses an enumerative approach to search for an optimal solution. At the end, the relief valve redesign example is applied to illustrate and justify the newly developed method components.

scholarly journals Prioritized optimization by Nash games : towards an adaptive multi-objective strategy

2021 ◽  
Vol 71 ◽  
pp. 54-63
Author(s):  
Jean-Antoine Désidéri ◽  
Régis Duvigneau
Keyword(s):  
Optimal Solution ◽  
Optimization Method ◽  
Cost Functions ◽  
Second Phase ◽  
Two Phase ◽  
Nash Games ◽  
Multi Objective ◽  
Business Jet ◽  
Decreasing Functions

This work is part of the development of a two-phase multi-objective differentiable optimization method. The first phase is classical: it corresponds to the optimization of a set of primary cost functions, subject to nonlinear equality constraints, and it yields at least one known Pareto-optimal solution xA*. This study focuses on the second phase, which is introduced to permit to reduce another set of cost functions, considered as secondary, by the determination of a continuum of Nash equilibria, {x̅ε} (ε≥ 0), in a way such that: firstly, x̅0=xA* (compatibility), and secondly, for ε sufficiently small, the Pareto-optimality condition of the primary cost functions remains O(ε2), whereas the secondary cost functions are linearly decreasing functions of ε. The theoretical results are recalled and the method is applied numerically to a Super-Sonic Business Jet (SSBJ) sizing problem to optimize the flight performance.

Peristaltic Carreau-Yasuda nanofluid flow and mixed heat transfer analysis in an asymmetric vertical and tapered wavy wall channel

2020 ◽  
Vol 1 (1) ◽  
pp. 128-140 ◽  
Author(s):  
Mohammad Hatami ◽  
◽  
D Jing ◽  
Keyword(s):  
Heat Transfer ◽  
Least Square Method ◽  
Weissenberg Number ◽  
Least Square ◽  
Heat Transfer Analysis ◽  
Phase Method ◽  
Nanofluid Flow ◽  
Two Phase ◽  
Nanoparticles Concentration ◽  
The Right

In this study, two-phase asymmetric peristaltic Carreau-Yasuda nanofluid flow in a vertical and tapered wavy channel is demonstrated and the mixed heat transfer analysis is considered for it. For the modeling, two-phase method is considered to be able to study the nanoparticles concentration as a separate phase. Also it is assumed that peristaltic waves travel along X-axis at a constant speed, c. Furthermore, constant temperatures and constant nanoparticle concentrations are considered for both, left and right walls. This study aims at an analytical solution of the problem by means of least square method (LSM) using the Maple 15.0 mathematical software. Numerical outcomes will be compared. Finally, the effects of most important parameters (Weissenberg number, Prandtl number, Brownian motion parameter, thermophoresis parameter, local temperature and nanoparticle Grashof numbers) on the velocities, temperature and nanoparticles concentration functions are presented. As an important outcome, on the left side of the channel, increasing the Grashof numbers leads to a reduction in velocity profiles, while on the right side, it is the other way around.

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