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Determining the pricing strategy for different preference structures for the earth observation satellite scheduling problem through simulation and VIKOR

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Abstract

This paper presents a method by which decision-makers of the Earth observation satellite operations can coordinate pricing and operational decisions. The pricing of satellite images is complex due to uncertainty and high combinatorial complexity in the scheduling, and the high number of evaluation criteria associated with the customers’ image requests. Likewise, any price changes will change the final schedule due to the complex scheduling procedure and preference reflected in the scoring, and understanding how is challenging. In addition, the changes can be very scenario-specific, so a change that seems beneficial in one scenario can lead to other outcomes in others. Therefore, this paper poses a method with which the satellite operator through simulation can investigate the robustness and combined effect of preference and pricing in order to select the pricing strategy that emphasizes the chosen preference structure the best while still finding a compromise on conflicting objectives related to profit, quantity, quality, etc. More specifically, the proposed method allows the satellite operators to take advantage of the scheduling flexibility through the decisions they control, i.e., price and preference structure.

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Authors and Affiliations

  1. Department of Materials and Production, Aalborg University, Aalborg, 9220, Denmark

    Alex Elkjær Vasegaard, Peter Nielsen & Subrata Saha

  2. Department of Industrial Engineering and Institute for Industrial Systems Innovation, Seoul National University, Gwanak-gu, Republic of Korea

    Ilkyeong Moon

  3. Department of Industrial Engineering, Seoul National University, Seoul, Republic of Korea

    Ilkyeong Moon

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  1. Alex Elkjær Vasegaard
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  2. Ilkyeong Moon
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  3. Peter Nielsen
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  4. Subrata Saha
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Correspondence to Subrata Saha.

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Appendices

Appendix 1: Pre-processing of system

The pre-processing of the system is highly connected to the scenario generation as it ultimately converts the customer database and satellite information into a problem scenario. In short, it identifies all feasible imaging attempts for the satellite and defines the constraints between all attempts. It does this by converting the satellite path into a grid of satellite action points. Each point identifies which requests are reachable and feasible according to the satellite capabilities and customer requirements. After that, all other relevant information (sun elevation, angle, area, cloud coverage) is obtained. In Figs. 5 and 6 the average characteristics of the generated scenarios can be seen. In the works of Elkjaer Vasegaard and Nielsen (2021), an overview of how the pre-processing is improved can be seen.

Fig. 5
figure 5

Characteristics of a single scenario generated in the planning horizon at 12th October 2020 18:00–22:00

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Fig. 6
figure 6

Characteristics of 100 different scenarios generated between the 12th and 13th of October 2020 at 12:00

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Appendix 2: VIKOR and Shannon entropy tables

See Tables 8, 9, 10 and 11.

Table 8 Threshold values for the three preference profiles utilized in the ELECTRE-III scoring approach. Note, q represents indifference, p represents preference, and v represents veto threshold
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Table 9 S, R, and Q indices and the corresponding rank
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Table 10 Weights for pricing specifications derived through Shannon entropy
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Table 11 The average performance measures for the different pricing specifications of area pricing strategy found through simulation
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Vasegaard, A.E., Moon, I., Nielsen, P. et al. Determining the pricing strategy for different preference structures for the earth observation satellite scheduling problem through simulation and VIKOR. Flex Serv Manuf J 35, 945–973 (2023). https://doi.org/10.1007/s10696-022-09444-z

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