OPTIMAL MANPOWER PLANNING DECISION WITH SINGLE EMPLOYEE TYPE CONSIDERING MINIMAL EMPLOYMENT PERIOD CONSTRAINT

In this paper, we investigate a manpower planning problem with single employee type over a long planning horizon. The dynamic demand for manpower must be fulfilled by allocating enough number of employees and each employee has a minimal employment period. A cost objective is concerned where the costs for every employee include salary, recruitment and dismissal costs, in particular, setup cost when recruitment activity occurs in one period. In this paper we first formulate the problem as a dynamic programming model. Then we derive properties of the problem and propose an algorithm to minimize the total manpower-related cost over the entire planning horizon. Next we discuss the influence on the optimal states of changing some parameters and provide the sensitivity analysis of the optimal states concerning the future demands. Finally, we report computational results to illustrate the correctness of the approach and to analyze the influence on the optimal states of changing parameters or changing future demands.

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Fleet Planning Decision-Making: Two-Stage Optimization with Slot Purchase

Journal of Optimization ◽

10.1155/2016/8089794 ◽

2016 ◽

Vol 2016 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Lay Eng Teoh ◽

Hooi Ling Khoo

Keyword(s):

Programming Model ◽

Planning Horizon ◽

Profit Margin ◽

Planning Problem ◽

Illustrative Case ◽

Two Stage ◽

Fleet Planning ◽

Novel Approach ◽

Planning Decision ◽

Service Frequency

Essentially, strategic fleet planning is vital for airlines to yield a higher profit margin while providing a desired service frequency to meet stochastic demand. In contrast to most studies that did not consider slot purchase which would affect the service frequency determination of airlines, this paper proposes a novel approach to solve the fleet planning problem subject to various operational constraints. A two-stage fleet planning model is formulated in which the first stage selects the individual operating route that requires slot purchase for network expansions while the second stage, in the form of probabilistic dynamic programming model, determines the quantity and type of aircraft (with the corresponding service frequency) to meet the demand profitably. By analyzing an illustrative case study (with 38 international routes), the results show that the incorporation of slot purchase in fleet planning is beneficial to airlines in achieving economic and social sustainability. The developed model is practically viable for airlines not only to provide a better service quality (via a higher service frequency) to meet more demand but also to obtain a higher revenue and profit margin, by making an optimal slot purchase and fleet planning decision throughout the long-term planning horizon.

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Dynamic Network Planning of Underground Logistics System on Uncertainty Graph

Mathematical Problems in Engineering ◽

10.1155/2019/1979275 ◽

2019 ◽

Vol 2019 ◽

pp. 1-13 ◽

Cited By ~ 1

Author(s):

YiHua Zhong ◽

ShiMing Luo ◽

Min Bao ◽

XiaoDie Lv

Keyword(s):

Dynamic Programming ◽

Programming Model ◽

Network Planning ◽

Dynamic Network ◽

Planning Problem ◽

Uncertainty Measure ◽

Uncertain Graph ◽

Logistics System ◽

Nanjing City ◽

Dynamic Programming Model

When designing the underground logistics system, it is necessary to consider the uncertainty of logistics nodes, high cost, and high risk. This paper employed the theories of uncertain graph and dynamic programming to solve the network planning problem of underground logistics system. Firstly, we proposed the concepts of uncertainty measure matrix and vertices structure uncertainty graph by using uncertainty measure and uncertainty graph. Secondly, vertices structure uncertainty graph of the underground logistics system was constructed based on our proposed vertices structure uncertainty graph and the uncertainty of logistics nodes. Thirdly, the dynamic programming model of the underground logistics system was established, and its solution algorithm was also designed by improving simulated annealing. Finally, the correctness and feasibility of the method was validated by using a numerical example of the underground logistics system in Xianlin district, Nanjing City in China.

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Production Planning Problem of a Two-Level Supply Chain with Production-Time-Dependent Products

Applied Sciences ◽

10.3390/app11209687 ◽

2021 ◽

Vol 11 (20) ◽

pp. 9687

Author(s):

Jun-Hee Han ◽

Ju-Yong Lee ◽

Bongjoo Jeong

Keyword(s):

Supply Chain ◽

Production Planning ◽

Programming Model ◽

Planning Horizon ◽

Mixed Integer ◽

Planning Problem ◽

Manufacturing Plant ◽

Production Lines ◽

Multiple Production ◽

Production Planning Problem

This study considers a production planning problem with a two-level supply chain consisting of multiple suppliers and a manufacturing plant. Each supplier that consists of multiple production lines can produce several types of semi-finished products, and the manufacturing plant produces the finished products using the semi-finished products from the suppliers to meet dynamic demands. In the suppliers, different types of semi-finished products can be produced in the same batch, and products in the same batch can only be started simultaneously (at the same time) even if they complete at different times. The purpose of this study is to determine the selection of suppliers and their production lines for the production of semi-finished products for each period of a given planning horizon, and the objective is to minimize total costs associated with the supply chain during the whole planning horizon. To solve this problem, we suggest a mixed integer programming model and a heuristic algorithm. To verify performance of the algorithm, a series of tests are conducted on a number of instances, and the results are presented.

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A new mathematical model for determining optimal workforce planning of pilots in an airline company

Complex & Intelligent Systems ◽

10.1007/s40747-021-00386-x ◽

2021 ◽

Author(s):

İbrahim Zeki Akyurt ◽

Yusuf Kuvvetli ◽

Muhammet Deveci ◽

Harish Garg ◽

Mert Yuzsever

Keyword(s):

Mathematical Model ◽

Workforce Planning ◽

Resource Planning ◽

Planning Horizon ◽

Mixed Integer ◽

Planning Problem ◽

Real World Data ◽

Planning Decision ◽

Airline Company

AbstractThis study aims to model a workforce-planning problem of pilot roles which include captain and first officer in an airline company and to make an efficient plan having maximal utilization of minimum workforce requirements. To tackle this problem, a mixed integer programming based a new mathematical model is proposed. The model considers different conditions such as employing pilots with different skill types, resignations, retirements, holidays of pilots, transitions between different skills regarding needs of the demands during the planning horizon. The application of the proposed approach is investigated using a case study with real-world data from an airline company in Turkey. The results show that a company can use transitions instead of new employment and this is a more suitable medium-term production and human resource planning decision.

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A Multiperiod Vehicle Lease Planning for Urban Freight Consolidation Network

Mathematical Problems in Engineering ◽

10.1155/2015/921482 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Woosuk Yang ◽

Taesu Cheong ◽

Sang Hwa Song

Keyword(s):

Programming Model ◽

Planning Horizon ◽

Planning Problem ◽

Transportation Services ◽

Urban Freight ◽

Urban Freight Transport ◽

Freight Consolidation ◽

Lagrangian Heuristic ◽

Time Restriction

This paper considers a multiperiod vehicle lease planning problem for urban freight consolidation centers (UFCCs) in the urban freight transport network where short-term-leased and long-term-leased vehicles are hired together. The objective is to allocate the two kinds of leased vehicles optimally for direct transportation services from the associated origin node to the associated UFCC or from the associated UFCC to the associated destinations so as to satisfy a given set of period-to-period freight demands over a given planning horizon at total minimum vehicle allocation cost subject to demand-dependent transportation time restriction. The problem is formulated as an integer programming model and proven to be NP-hard in a strong sense. Thus, a Lagrangian heuristic is proposed to find a good solution efficiently. Numerical experiments show that the proposed algorithm finds good lower and upper bounds within reasonable time.

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