What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Microeconomics
His primary scientific interests are in Mathematical optimization, Operations research, Product, Supply chain and Job shop scheduling.
Ping Ji is involved in the study of Mathematical optimization that focuses on Genetic algorithm in particular.
His biological study spans a wide range of topics, including Advanced planning and scheduling, Panel data, Data envelopment analysis and Container port.
His Data envelopment analysis study integrates concerns from other disciplines, such as Variety and Production.
In his work, Knowledge management, Information retrieval and Feature is strongly intertwined with Sentiment analysis, which is a subfield of Product.
Ping Ji has researched Supply chain in several fields, including Procurement and Operations management.
His most cited work include:
- The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis (384 citations)
- An Application of DEA Windows Analysis to Container Port Production Efficiency (257 citations)
- A hybrid genetic algorithm for the multi-depot vehicle routing problem (234 citations)
What are the main themes of his work throughout his whole career to date?
Ping Ji mainly focuses on Mathematical optimization, Job shop scheduling, Operations research, Genetic algorithm and Learning effect.
His work on Assignment problem as part of general Mathematical optimization research is frequently linked to Single-machine scheduling, Completion time and Tardiness, bridging the gap between disciplines.
When carried out as part of a general Job shop scheduling research project, his work on Flow shop scheduling and Group scheduling is frequently linked to work in Real-time computing, Scheduling and Heuristic, therefore connecting diverse disciplines of study.
Ping Ji usually deals with Operations research and limits it to topics linked to Linear programming and Integer programming.
His research integrates issues of Vehicle routing problem, Heuristics and Component in his study of Genetic algorithm.
His Component research integrates issues from Sequence, Electronic engineering, Mathematical model and Heuristic.
He most often published in these fields:
- Mathematical optimization (37.36%)
- Job shop scheduling (18.68%)
- Operations research (15.93%)
What were the highlights of his more recent work (between 2017-2021)?
- Supply chain (8.24%)
- Operations research (15.93%)
- Cloud computing (1.65%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Supply chain, Operations research, Cloud computing, Cyber-physical system and Job shop scheduling.
His Supply chain research incorporates themes from Procurement, Microeconomics and Commerce.
Ping Ji combines subjects such as Linear programming and Quality function deployment with his study of Operations research.
His Cyber-physical system study combines topics in areas such as Bridge, Media management and Systems engineering.
Job shop scheduling is intertwined with Scheduling, Mathematical optimization, Learning effect, Time complexity and Total cost in his research.
The study incorporates disciplines such as Sentiment analysis, Feature and Bayesian probability, Bayesian inference in addition to Product.
Between 2017 and 2021, his most popular works were:
- Cyber-physical integration for moving digital factories forward towards smart manufacturing: a survey (49 citations)
- An improved approach for failure mode and effect analysis involving large group of experts: An application to the healthcare field (46 citations)
- Optimal procurement decision with a carbon tax for the manufacturing industry (26 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Microeconomics
His primary areas of investigation include Supply chain, Procurement, Industrial organization, Carbon tax and Microeconomics.
In most of his Procurement studies, his work intersects topics such as Economic order quantity.
His Economic order quantity research includes elements of Supply and demand, Supply chain management, Supplier evaluation and Operations research.
His studies deal with areas such as Bargaining power, Contract manufacturer, Outsourcing and Bargaining problem as well as Industrial organization.
His Carbon tax research incorporates elements of General equilibrium theory, Dynamic pricing, Time horizon, Nash equilibrium and Pricing strategies.
His study in the field of Oligopoly, Information asymmetry and Common value auction is also linked to topics like Eauction and Emissions trading.
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