A simulation-based multi-objective optimization study of the fleet sizing problem in the offshore industry

2015 ◽  
Author(s):  
Hamidreza Eskandari ◽  
Ehsan Mahmoodi
Keyword(s):  
Multi Objective Optimization ◽  
Multi Objective ◽  
Fleet Sizing ◽  
Optimization Study ◽  
Simulation Based ◽  
Offshore Industry

scholarly journals A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification

2016 ◽  
Vol 48 ◽  
pp. 111-123 ◽  
Author(s):  
Vitor Basto-Fernandes ◽  
Iryna Yevseyeva ◽  
José R. Méndez ◽  
Jiaqi Zhao ◽  
Florentino Fdez-Riverola ◽  
...  
Keyword(s):  
Spam Filtering ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Study

Multi-Objective Optimization Based on TTR Interference Analysis

2013 ◽  
Vol 753-755 ◽  
pp. 1217-1220
Author(s):  
Da Wei Ji ◽  
Yi Huang ◽  
Qi Zhang
Keyword(s):  
Deep Water ◽  
Present Method ◽  
Critical Issue ◽  
Multi Objective Optimization ◽  
Interference Analysis ◽  
Multi Objective ◽  
Riser Design ◽  
Offshore Industry

Riser interference has become a critical issue in riser design with the progression of offshore industry into deep water. It indicates that the potential for interference between Top Tension Risers (TTR) depends not only on the Top Tension Factor (TTF), but also on the riser spacing size. For riser system, each impassive factor of interference could make a different effect (cost and safety), which is often incompatible. A Multi-Objective Optimization (MOO) method is proposed to harmonize the two incompatible objectives: cost and safety. Therefore, it greatly facilitates to adapt the present method to riser interference optimization. Example is given to demonstrate the effectiveness and robustness of the proposed method.

Efficient container stacking approach to improve handling: efficiency in Chinese rail–truck transshipment terminals

SIMULATION ◽  
2019 ◽  
Vol 96 (1) ◽  
pp. 3-15 ◽  
Author(s):  
Wang Li ◽  
Zhu Xiaoning ◽  
Xie Zhengyu
Keyword(s):  
Optimization Model ◽  
Experimental Results ◽  
Computational Experiments ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Container Stacking ◽  
Simulation Based ◽  
Allocation Preferences

An efficient container stacking approach is vital to the handling efficiency of container transshipment terminals. In this paper, by considering container allocation preferences and operation distance, the container stacking problem in rail–truck transshipment terminals has been formulated as a multi-objective optimization model to minimize container overlapping amounts and crane moving distance. A simulation-based algorithm implementing process has been developed to stack containers to the optimum positions. Computational experiments on data from a rail–truck transshipment terminal in China are conducted to test the efficiency of the proposed approach. Experimental results demonstrate that the container stacking approach is efficient and significant for improving handling efficiency in rail–truck transshipment terminals.

Multi-Objective Optimization for the Micro-Milling Process With Adaptive Data Modeling

2011 ◽  
Author(s):  
Xinyu Liu ◽  
Weihang Zhu ◽  
Victor Zaloom
Keyword(s):  
Surrogate Model ◽  
Data Modeling ◽  
Milling Process ◽  
Machining Process ◽  
Micro Milling ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Study ◽  
Machining Parameter

This paper presents a multi-objective optimization study for the micro-milling process with adaptive data modeling based on the process simulation. A micro-milling machining process model was developed and verified through our previous study. Based on the model, a set of simulation data was generated from a factorial design. The data was converted into a surrogate model with adaptive data modeling method. The model has three input variables: axial depth of cut, feed rate and spindle speed. It has two conflictive objectives: minimization of surface location error (which affects surface accuracy) and minimization of total tooling cost. The surrogate model is used in a multi-objective optimization study to obtain the Pareto optimal sets of machining parameters. The visual display of the non-dominated solution frontier allows an engineer to select a preferred machining parameter in order to get a lowest cost solution given the requirement from tolerance and accuracy. The contribution of this study is to provide a streamlined methodology to identify the preferred best machining parameters for micro-milling.

scholarly journals Multi-objective optimization of an industrial styrene reactor using Harmony Search Algorithm

2013 ◽  
pp. 190-196
Author(s):  
Saurabh Shukla ◽  
Ankit Anand
Keyword(s):  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Operating Conditions ◽  
Multi Objective Optimization ◽  
Industrial Practice ◽  
Multi Objective ◽  
Decision Variables ◽  
Optimization Study ◽  
Study Results

Multi-objective optimization of industrial styrene reactor is done using Harmony Search algorithm. Harmony search algorithm is a recently developed meta-heuristic algorithm which is inspired by musical improvisation process aimed towards obtaining the best harmony. Three objective functions – productivity, selectivity and yield are optimized to get best combination of decision variables for styrene reactor. All possible cases of single and multi-objective optimization have been considered. Pareto optimal sets are obtained as a result of the optimization study. Results reveal that optimized solution using harmony search algorithm gives better operating conditions than industrial practice.

scholarly journals Optimization Study on Turning Process by Using Taguchi-copras Method

2021 ◽  
Vol 309 ◽  
pp. 01010
Author(s):  
Do Duc Trung ◽  
Nguyen Huu Quang ◽  
Tran Quoc Hoang ◽  
Cao The Anh ◽  
Nguyen Hong Linh ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Removal Rate ◽  
Multi Objective Optimization ◽  
Turning Process ◽  
Nose Radius ◽  
Multi Objective ◽  
Optimization Study ◽  
Input Parameters ◽  
Cutting Velocity ◽  
Copras Method

In this article, a multi-objective optimization of turning process study is presented. Two output parameters of the turning process taken into consideration are surface roughness and Material Removal Rate (MRR). Taguchi method has been applied to design the experimental matrix with four input parameters including nose radius, cutting velocity, feed rate and cutting depth. Copras method has been employed to solve the multi-objective optimization problem. Finally, the optimal values of the input parameters have been determined to simultaneously ensure the two criteria of the minimum surface roughness and the maximum MRR.

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