Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan ...Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.展开更多
The inbound and outbound tasks for valuable imported ship outfitting items are operated by multiple automated guided vehicles(AGVs)simultaneously in the outfitting warehouse.Given the efficiency mismatch between trans...The inbound and outbound tasks for valuable imported ship outfitting items are operated by multiple automated guided vehicles(AGVs)simultaneously in the outfitting warehouse.Given the efficiency mismatch between transportation equipment and the lack of effective scheduling of AGVs,the objective of the studied scheduling problem is to minimize the total travel time cost of vehicles.A multi-AGV task scheduling model based on time window is established considering the loading constraints of AGVs and cooperation time window constraints of stackers.According to the transportation characteristics in the outfitting warehouse,this study pro-poses a conflict detection method for heavy forklift AGVs,and correspondingly defines a conflict penalty function.Furthermore,to comprehensively optimize travel time cost and conflict penalty,a hybrid genetic neighborhood search algorithm(GA-ANS)is proposed.Five neighborhood structures are designed,and adaptive selection opera-tors are introduced to enhance the ability of global search and local chemotaxis.Numerical experiments show that the proposed GA-ANS algorithm can effectively solve the problem even when the scale of the problem increases and the effectiveness of the vehicle conflict penalty strategy is analyzed.展开更多
Ship outfitting manufacturing starts from assembling outfitting, including pre-outfitting, general outfitting, dock outfitting and many other processes. The outfitting of ships runs through the whole process of ship b...Ship outfitting manufacturing starts from assembling outfitting, including pre-outfitting, general outfitting, dock outfitting and many other processes. The outfitting of ships runs through the whole process of ship building, and there are many kinds of outfitting parts, which easily leads to the omission of outfitting construction. The traditional outfitting mode can't meet the requirements of "shell outfitting and coating" integration of modern ship building and the construction standard of outfitting integrity. Based on this situation, this paper discusses the application of pallet management of ship outfitting parts.展开更多
A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such...A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.展开更多
Intermediate charging and sudden failure of automatic guided vehicles(AGVs)interrupt and severely affect the stability and efficiency of scheduling.Therefore,an AGV scheduling approach considering equipment failure an...Intermediate charging and sudden failure of automatic guided vehicles(AGVs)interrupt and severely affect the stability and efficiency of scheduling.Therefore,an AGV scheduling approach considering equipment failure and power management is proposed for outfitting warehouses.First,a power consumption model is established for AGVs performing transportation tasks.The powers for departure and task consumption are used to calculate the AGV charging and return times.Second,an optimization model for AGV scheduling is established to minimize the total transportation time.Different conditions are defined for the overhaul and minor repair of AGVs,and a scheduling strategy for responding to sudden failure is proposed.Finally,an algorithm is developed to solve the optimization model for a case study.The method can be used to plan the charging time and perform rescheduling under sudden failure to improve the robustness and dynamic response capability of AGVs.展开更多
With the development of artificial intelligence in recent decades, intelligent algorithms such as visual recognition and natural language processing have affected and will continue to affect our lives. A smart device ...With the development of artificial intelligence in recent decades, intelligent algorithms such as visual recognition and natural language processing have affected and will continue to affect our lives. A smart device designed to help people make wise decisions on dress through dialogue would be a very convenient tool. By using a color extraction algorithm and natural language processing methods, we have built an outfit planning chatbot, named Outfit Helper, that can help male users decide what to wear in order to dress well. According to our study, most users think that the Outfit Helper is a good choice for solving the clothing matching problem. This study shows that our lives can become much easier by developing and using artificial intelligence to help us choose our clothing.展开更多
对话A:I want to go try on these clothes.我想试穿这些衣服。B:What did you find?你发现了什么?A:I found some jeans,and a new blouse.我找到一些牛仔裤和一件新的衬衣。B:Go and try it on.那去试试看吧。A:What do you think?你...对话A:I want to go try on these clothes.我想试穿这些衣服。B:What did you find?你发现了什么?A:I found some jeans,and a new blouse.我找到一些牛仔裤和一件新的衬衣。B:Go and try it on.那去试试看吧。A:What do you think?你觉得怎么样?B:I love that blouse on you.我觉得挺不错的。展开更多
基金supported in part by the High-tech ship scientific research project of the Ministry of Industry and Information Technology of the People’s Republic of China,and the National Nature Science Foundation of China(Grant No.71671113)the Science and Technology Department of Shaanxi Province(No.2020GY-219)the Ministry of Education Collaborative Project of Production,Learning and Research(No.201901024016).
文摘Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.
基金China Ministry of Industry and Information Technology for High-Tech Ship Project。
文摘The inbound and outbound tasks for valuable imported ship outfitting items are operated by multiple automated guided vehicles(AGVs)simultaneously in the outfitting warehouse.Given the efficiency mismatch between transportation equipment and the lack of effective scheduling of AGVs,the objective of the studied scheduling problem is to minimize the total travel time cost of vehicles.A multi-AGV task scheduling model based on time window is established considering the loading constraints of AGVs and cooperation time window constraints of stackers.According to the transportation characteristics in the outfitting warehouse,this study pro-poses a conflict detection method for heavy forklift AGVs,and correspondingly defines a conflict penalty function.Furthermore,to comprehensively optimize travel time cost and conflict penalty,a hybrid genetic neighborhood search algorithm(GA-ANS)is proposed.Five neighborhood structures are designed,and adaptive selection opera-tors are introduced to enhance the ability of global search and local chemotaxis.Numerical experiments show that the proposed GA-ANS algorithm can effectively solve the problem even when the scale of the problem increases and the effectiveness of the vehicle conflict penalty strategy is analyzed.
文摘Ship outfitting manufacturing starts from assembling outfitting, including pre-outfitting, general outfitting, dock outfitting and many other processes. The outfitting of ships runs through the whole process of ship building, and there are many kinds of outfitting parts, which easily leads to the omission of outfitting construction. The traditional outfitting mode can't meet the requirements of "shell outfitting and coating" integration of modern ship building and the construction standard of outfitting integrity. Based on this situation, this paper discusses the application of pallet management of ship outfitting parts.
基金Shanghai Frontier Science Research Center for Modern Textiles,Donghua University,ChinaOpen Project of Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment,Zhengzhou University of Light Industry,China(No.IM202303)National Key Research and Development Program of China(No.2019YFB1706300)。
文摘A personalized outfit recommendation has emerged as a hot research topic in the fashion domain.However,existing recommendations do not fully exploit user style preferences.Typically,users prefer particular styles such as casual and athletic styles,and consider attributes like color and texture when selecting outfits.To achieve personalized outfit recommendations in line with user style preferences,this paper proposes a personal style guided outfit recommendation with multi-modal fashion compatibility modeling,termed as PSGNet.Firstly,a style classifier is designed to categorize fashion images of various clothing types and attributes into distinct style categories.Secondly,a personal style prediction module extracts user style preferences by analyzing historical data.Then,to address the limitations of single-modal representations and enhance fashion compatibility,both fashion images and text data are leveraged to extract multi-modal features.Finally,PSGNet integrates these components through Bayesian personalized ranking(BPR)to unify the personal style and fashion compatibility,where the former is used as personal style features and guides the output of the personalized outfit recommendation tailored to the target user.Extensive experiments on large-scale datasets demonstrate that the proposed model is efficient on the personalized outfit recommendation.
基金Supported by the China High-Tech Ship Project of the Ministry of Industry and Information Technology under Grant No.[2019]360.
文摘Intermediate charging and sudden failure of automatic guided vehicles(AGVs)interrupt and severely affect the stability and efficiency of scheduling.Therefore,an AGV scheduling approach considering equipment failure and power management is proposed for outfitting warehouses.First,a power consumption model is established for AGVs performing transportation tasks.The powers for departure and task consumption are used to calculate the AGV charging and return times.Second,an optimization model for AGV scheduling is established to minimize the total transportation time.Different conditions are defined for the overhaul and minor repair of AGVs,and a scheduling strategy for responding to sudden failure is proposed.Finally,an algorithm is developed to solve the optimization model for a case study.The method can be used to plan the charging time and perform rescheduling under sudden failure to improve the robustness and dynamic response capability of AGVs.
文摘With the development of artificial intelligence in recent decades, intelligent algorithms such as visual recognition and natural language processing have affected and will continue to affect our lives. A smart device designed to help people make wise decisions on dress through dialogue would be a very convenient tool. By using a color extraction algorithm and natural language processing methods, we have built an outfit planning chatbot, named Outfit Helper, that can help male users decide what to wear in order to dress well. According to our study, most users think that the Outfit Helper is a good choice for solving the clothing matching problem. This study shows that our lives can become much easier by developing and using artificial intelligence to help us choose our clothing.
文摘对话A:I want to go try on these clothes.我想试穿这些衣服。B:What did you find?你发现了什么?A:I found some jeans,and a new blouse.我找到一些牛仔裤和一件新的衬衣。B:Go and try it on.那去试试看吧。A:What do you think?你觉得怎么样?B:I love that blouse on you.我觉得挺不错的。
