Abstract

Most of serious and major accidents that happened during the production procedure of process industry are caused by improper equipment operations, which is further owing to inappropriate human resources allocation and ignorance of individual competencies differences. In order to take both of competency disadvantage and adjustment requirement into consideration, we use an inverse optimization method to solve a human resource allocation problem, and furthermore, adjust equipment operating parameters to make the per-defined settings optimized, such as the total number of jobs, security-related parameters and so on.In the solving process, firstly a standard competence hierarchy system is conducted; secondly we propose an assessment method according to disadvantage structure; thirdly we use inverse optimization method to solve the problem and optimize the predefined allocation plan. Lastly, we give an example to prove its feasibility and effectiveness. In this paper a novel formulation of human resource allocation problem is proposed, in which some of main individual characteristics are considered and described mathematically, including psychology, behaviour and characteristics diged from them such as weakness. The other contribution of this paper is using inverse optimization to adjust parameters based on the given ideal allocation plan. Both of these propositions have a positive significance on promoting development and security construction for process industries.This research incorporates the academic thinking of inverse optimization, it not only puts psychology and behavior into optimization model, but also data mines weakness characteristics under the psychology and behavior data, and find a new way to introducing the weakness characteristics into decision making model. It provides a new thought for the following decision making problem, that is the ideal decision plan is known, and optimization parameters are changeable. It promotes the combining of psychology, behavior and operations research, it is good for process industries to develop in a safety and efficiency way.

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