scholarly journals Deterministic Conversion of Uncertain Manpower Planning Optimization Problem

2018 ◽  
Vol 26 (5) ◽  
pp. 2748-2757 ◽  
Author(s):  
Bo Li ◽  
Yuanguo Zhu ◽  
Yufei Sun ◽  
Grace Aw ◽  
Kok Lay Teo
Keyword(s):  
Optimization Problem ◽  
Manpower Planning ◽  
Planning Optimization

Production Planning Optimization in F Company: A Scheduling Theory Case Study

2013 ◽  
Vol 655-657 ◽  
pp. 1646-1649 ◽  
Author(s):  
Chi Zhang ◽  
Zhen He ◽  
Yuan Peng Ruan
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Optimization Problem ◽  
Assembly Line ◽  
Scheduling Theory ◽  
Scheduling Model ◽  
Planning Optimization ◽  
Optimization Methodology ◽  
Optimum Production

Scheduling is an effective optimization methodology which has been widely used for production planning. This paper presents a scheduling model to optimize the output of an assembly line in F Semiconductor Company in Tianjin, China. The authors formulate the optimization problem as linear programming. The model and its implementation are described in detail in this article. The optimum production allocations have been founded by the scheduling model and the output has been increased.

An Industry Maintenance Planning Optimization Problem Using CMA-VNS and Its Variations

2021 ◽  
pp. 429-443
Author(s):  
Anna Zholobova ◽  
Yefim Zholobov ◽  
Ivan Polyakov ◽  
Ovanes Petrosian ◽  
Tatyana Vlasova
Keyword(s):  
Optimization Problem ◽  
Maintenance Planning ◽  
Planning Optimization

scholarly journals Split Common Coincidence Point Problem: A Formulation Applicable to (Bio)Physically-Based Inverse Planning Optimization

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2086
Author(s):  
Charles E. Chidume ◽  
Lois C. Okereke
Keyword(s):  
Optimization Problem ◽  
Coincidence Point ◽  
Point Problem ◽  
Optimization Approach ◽  
Inverse Planning ◽  
Clinical Criteria ◽  
Planning Optimization ◽  
Physically Based ◽  
Treatment Plans ◽  
Optimized Treatment

Inverse planning is a method of radiotherapy treatment planning where the care team begins with the desired dose distribution satisfying prescribed clinical objectives, and then determines the treatment parameters that will achieve it. The variety in symmetry, form, and characteristics of the objective functions describing clinical criteria requires a flexible optimization approach in order to obtain optimized treatment plans. Therefore, we introduce and discuss a nonlinear optimization formulation called the split common coincidence point problem (SCCPP). We show that the SCCPP is a suitable formulation for the inverse planning optimization problem with the flexibility of accommodating several biological and/or physical clinical objectives. Also, we propose an iterative algorithm for approximating the solution of the SCCPP, and using Bregman techniques, we establish that the proposed algorithm converges to a solution of the SCCPP and to an extremum of the inverse planning optimization problem. We end with a note on useful insights on implementing the algorithm in a clinical setting.

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