지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2024.10
- 수록면
- 134 - 157 (24page)
이용수
초록· 키워드
오류제보하기
As on-demand platforms continue to grow, managing workforce uncertainty due to gig workers has become increasingly challenging, leading to extensive research into scheduling solutions. Many platforms utilize hybrid and centralized scheduling with pre-scheduled couriers to reduce operational uncertainties;
however, these couriers still have uncertainty in their work participation. In this study, we propose a courier staffing and scheduling model that captures this uncertainty by learning it through a single-layer perceptron model and incorporating it into a mathematical optimization model via a technology matrix.We also consider the differing show-up rates and job proficiencies of committed couriers-those dedicated to a single platform-and ad-hoc couriers. To mitigate the increased computational complexity caused by the technology matrix, we applied asynchronous projective hedging algorithm and scenario bundling to enhance convergence speed. We validated the economic efficiency of our proposed model using a work participation simulator based on real-world data. This validation showed that operating costs
were reduced by around 4%, and the frequency of service disruptions due to workforce shortages also decreased.
however, these couriers still have uncertainty in their work participation. In this study, we propose a courier staffing and scheduling model that captures this uncertainty by learning it through a single-layer perceptron model and incorporating it into a mathematical optimization model via a technology matrix.We also consider the differing show-up rates and job proficiencies of committed couriers-those dedicated to a single platform-and ad-hoc couriers. To mitigate the increased computational complexity caused by the technology matrix, we applied asynchronous projective hedging algorithm and scenario bundling to enhance convergence speed. We validated the economic efficiency of our proposed model using a work participation simulator based on real-world data. This validation showed that operating costs
were reduced by around 4%, and the frequency of service disruptions due to workforce shortages also decreased.
목차
Abstract
1. Introduction
2. Literature Review
3. Problem Formulation
4. Methodology
5. Numerical Experiments
6. Conclusion
References
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
A systemic literature review for ergonomic courier service work
대한산업공학회 춘계공동학술대회 논문집
2022 .06
-
Optimal Service Price and Wage in Meal Delivery Platform with Multiple Types of Customers and Couriers
대한산업공학회 추계학술대회 논문집
2022 .11
-
스마트 무인 택배함
한국컴퓨터정보학회 학술발표논문집
2020 .01
-
택배 근로자 배송 작업의 부하 정량화
대한인간공학회지
2023 .02
-
작업 조건에 따른 택배 배송 작업가능시간에 관한 연구
대한인간공학회 학술대회논문집
2022 .10
-
스마트 모빌리티를 활용한 Last Mile Delivery 개선방안에 관한 연구
한국자동차공학회 추계학술대회 및 전시회
2019 .11
-
차세대 건물 배송 로봇 시스템
대한전자공학회 학술대회
2021 .11
-
소셜 네트워크 빅데이터 기반 택배업체 고객만족도에 관한 연구
한국전자거래학회지
2016 .11
-
빛나는 사과 나무
한국기계가공학회 춘추계학술대회 논문집
2020 .11
-
Box Stacker Solution for Loading Process Using Deep Reinforcement Learning
한국통신학회 학술대회논문집
2022 .02
-
택배 서비스 네트워크 설계를 위한 수리적 모형 개발
대한산업공학회지
2019 .06
-
Procurement scheduling under supply and demand uncertainty : Case study for comparing classical, reactive, and proactive scheduling
제어로봇시스템학회 국제학술대회 논문집
2015 .10
-
택배 근로자 배송 작업의 부하 정량화
대한인간공학회 학술대회논문집
2022 .04
-
A Novel Approach for Task Scheduling in Parallel Computing using Priority Attributes
SmartCR
2015 .08
-
Static Task Scheduling Algorithm with Minimum Distance for Multiprocessor System (STMD)
SmartCR
2015 .04
-
An ergonomic assessment of the push and pull of couriers" delivery trolleys
대한산업공학회 추계학술대회 논문집
2023 .11
-
Arbitrary Processor Network Scheduling Algorithms in Parallel Computing
SmartCR
2015 .06
-
무선 애드혹 네트워크에서 우선순위를 고려한 분산 노드 스케줄링
제어로봇시스템학회 논문지
2020 .02
-
Robust scheduling for a disruption risk
대한산업공학회 추계학술대회 논문집
2022 .11
-
Rider Scheduling In Last-mile Delivery: Incorporating The Fluctuating Demand And Show-up Rate Dynamics
대한산업공학회 추계학술대회 논문집
2023 .11
이 논문과 함께 이용한 논문
컨볼루션 오토인코더와 다층 퍼셉트론을 이용한 냉장고 사이클 진공도 시계열 이상 패턴 탐지 및 분류
정재현
,
노유정
,
강영진
외 2명
대한산업공학회지
2025
.02
로봇 조립 특징 형상 분류를 위한 3D CNN 개발
도남철
,
한효녕
,
조준면
대한산업공학회지
2024
.12
SYnet: 4D Convolutional Neural Network-Based Maintenance Lift Vehicle Demand Prediction Model for a Large Shipyard
Kyuheon Jung
,
Sungchul Choi
,
Sion Jang
외 1명
Industrial Engineering & Management Systems
2024
.06
상관관계 분석 및 데이터 증강을 활용한 반도체 설비 고장 감지
백민재
,
김성범
대한산업공학회지
2024
.06
Self-Assured Deep Learning with Minimum Pre-Labeled Data for Wafer Pattern Classification
Shu-Kai S. Fan
,
Du-Ming Tsai
,
Ya-Fang Shih
대한산업공학회 춘계공동학술대회 논문집
2024
.05
최근 본 자료
댓글(0)
0
UCI(KEPA) : I410-151-25-02-091160734