1,507 research outputs found
Changing Bases: Multistage Optimization for Matroids and Matchings
This paper is motivated by the fact that many systems need to be maintained
continually while the underlying costs change over time. The challenge is to
continually maintain near-optimal solutions to the underlying optimization
problems, without creating too much churn in the solution itself. We model this
as a multistage combinatorial optimization problem where the input is a
sequence of cost functions (one for each time step); while we can change the
solution from step to step, we incur an additional cost for every such change.
We study the multistage matroid maintenance problem, where we need to maintain
a base of a matroid in each time step under the changing cost functions and
acquisition costs for adding new elements. The online version of this problem
generalizes online paging. E.g., given a graph, we need to maintain a spanning
tree at each step: we pay for the cost of the tree at time
, and also for the number of edges changed at
this step. Our main result is an -approximation, where is
the number of elements/edges and is the rank of the matroid. We also give
an approximation for the offline version of the problem. These
bounds hold when the acquisition costs are non-uniform, in which caseboth these
results are the best possible unless P=NP.
We also study the perfect matching version of the problem, where we must
maintain a perfect matching at each step under changing cost functions and
costs for adding new elements. Surprisingly, the hardness drastically
increases: for any constant , there is no
-approximation to the multistage matching maintenance
problem, even in the offline case
Design of Closed Loop Supply Chains
Increased concern for the environment has lead to new techniques to design products and supply chains that are both economically and ecologically feasible. This paper deals with the product - and corresponding supply chain design for a refrigerator. Literature study shows that there are many models to support product design and logistics separately, but not in an integrated way. In our research we develop quantitative modelling to support an optimal design structure of a product, i.e. modularity, repairability, recyclability, as well as the optimal locations and goods flows allocation in the logistics system. Environmental impacts are measured by energy and waste. Economic costs are modelled as linear functions of volumes with a fixed set-up component for facilities. We apply this model using real life R&D data of a Japanese consumer electronics company. The model is run for different scenarios using different parameter settings such as centralised versus decentralised logistics, alternative product designs, varying return quality and quantity, and potential environmental legislation based on producer responsibility.supply chain management;reverse logistics;facility location;network design;product design
๊ณต์ปจํ ์ด๋๊ด๋ฆฌ ๊ธฐ๋ฒ์ ํ์ฉํ ํจ์จ์ ์ธ ์ปจํ ์ด๋ ๊ณต๊ธ๋ง
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ๊ณต๊ณผ๋ํ ์ฐ์
๊ณตํ๊ณผ, 2021. 2. ๋ฌธ์ผ๊ฒฝ.Due to a remarkable surge in global trade volumes led by maritime transportation, shipping companies should make a great effort in managing their container flows especially in case of carrier-owned containers. To do so, they comprehensively implement empty container management strategies and accelerate the flows in a cost- and time-efficient manner to minimize total relevant costs while serving the maximal level of customers demands. However, many critical issues in container flows universally exist due to high uncertainty in reality and hinder the establishment of an efficient container supply chain.
In this dissertation, we fully discuss such issues and provide mathematical models along with specific solution procedures. Three types of container supply chain are presented in the following: (i) a two-way four-echelon container supply chain; (ii) a laden and empty container supply chain under decentralized and centralized policies; (iii) a reliable container supply chain under disruption. These models explicitly deal with high risks embedded in a container supply chain and their computational experiments offer underlying managerial insights for the management in shipping companies.
For (i), we study empty container management strategy in a two-way four-echelon container supply chain for bilateral trade between two countries. The strategy reduces high maritime transportation costs and long delivery times due to transshipment. The impact of direct shipping is investigated to determine the number of empty containers to be repositioned among selected ports, number of leased containers, and route selection to satisfy the demands for empty and laden containers for exporters and importers in two regions. A hybrid solution procedure based on accelerated particle swarm optimization and heuristic is presented, and corresponding results are compared.
For (ii), we introduce the laden and empty container supply chain model based on three scenarios that differ with regard to tardiness in the return of empty containers and the decision process for the imposition of fees with the goal of determining optimal devanning times. The effectiveness of each type of policy - centralized versus decentralized - is determined through computational experiments that produce key performance measures including the on-time return ratio. Useful managerial insights on the implementation of these polices are derived from the results of sensitivity analyses and comparative studies.
For (iii), we develop a reliability model based on container network flow while also taking into account expected transportation costs, including street-turn and empty container repositioning costs, in case of arc- and node-failures. Sensitivity analyses were conducted to analyze the impact of disruption on container supply chain networks, and a benchmark model was used to determine disruption costs. More importantly, some managerial insights on how to establish and maintain a reliable container network flow are also provided.ํด์ ์์ก์ด ์ฃผ๋ํจ์ผ๋ก์จ ์ ์ธ๊ณ ๋ฌด์ญ๋์ด ๊ธ์ฆํ๊ธฐ ๋๋ฌธ์ ํ์ฌ ์์ ์ปจํ
์ด๋๋ ์ปจํ
์ด๋ ํ๋ฆ์ ๊ด๋ฆฌํ๋ ๋ฐ ๋ง์ ๋
ธ๋ ฅ์ ๊ธฐ์ธ์ฌ์ผ ํ๋ค. ์ด๋ฅผ ์ํด ๊ณต ์ปจํ
์ด๋ ๊ด๋ฆฌ ์ ๋ต์ ํฌ๊ด์ ์ผ๋ก ๊ตฌํํ๊ณ ํจ์จ์ ์ธ ์์ก ๋น์ฉ ๋ฐ ์๊ฐ ์ ๊ฐ ๋ฐฉ์์ผ๋ก ์ปจํ
์ด๋ ํ๋ฆ์ ์ํํ ํ์ฌ ๊ด๋ จ ์ด๋น์ฉ์ ์ต์ํํ๋ ๋์์ ๊ณ ๊ฐ์ ์์๋ฅผ ์ต๋ํ ์ถฉ์กฑํ๊ฒ ๋๋ค. ๊ทธ๋ฌ๋ ํ์ค์์๋ ๋์ ๋ถํ์ค์ฑ ๋๋ฌธ์ ์ปจํ
์ด๋ ํ๋ฆ์ ๋ํ ๋ง์ ์ฃผ์ํ ์ด์๊ฐ ๋ณดํธ์ ์ผ๋ก ์กด์ฌํ๊ณ ํจ์จ์ ์ธ ์ปจํ
์ด๋ ๊ณต๊ธ๋ง ๊ตฌ์ถ์ ๋ฐฉํดํ๋ค.
๋ณธ ๋
ผ๋ฌธ์์๋ ์ด๋ฌํ ์ด์์ ๋ํด ์ ๋ฐ์ ์ผ๋ก ๋
ผ์ํ๊ณ ์ ์ ํ ํด๋ฒ๊ณผ ํจ๊ป ์๋ฆฌ ๋ชจํ์ ์ ๊ณตํ๋ค. ์ด๋ฅผ ์ํด ์ธ ๊ฐ์ง ์ ํ์ ์ปจํ
์ด๋ ๊ณต๊ธ๋ง์ ๋ค๋ฃฌ๋ค. ๋จผ์ (i) ์๋ฐฉํฅ ๋ค ๋จ๊ณ ์ปจํ
์ด๋ ๊ณต๊ธ๋ง, (ii) ๋ถ๊ถํ ๋ฐ ์ค์ ์ง์คํ ์ ์ฑ
์ ๋ฐ๋ฅธ ์ โ๊ณต ์ปจํ
์ด๋ ๊ณต๊ธ๋ง; ๊ทธ๋ฆฌ๊ณ (iii) disruption ์ํฉ ์์์ ์ ๋ขฐ์ฑ์ ๊ณ ๋ คํ๋ ์ปจํ
์ด๋ ๊ณต๊ธ๋ง์ด๋ค. ๋ณธ ๋
ผ๋ฌธ์์ ์ ์ํ ์ธ ๊ฐ์ง ๋ชจํ์ ์ปจํ
์ด๋ ๊ณต๊ธ๋ง์ ๋ด์ฌ ๋ ๋์ ์ํ์ ์ง์ ๋ค๋ฃจ๋ฉฐ ๊ณ์ฐ ์คํ์ ํด์ด ํ์ฌ์ ๊ฒฝ์์ง์ด๋ ๊ด๊ณ์๋ฅผ ์ํด ์ฃผ์ํ ๊ด๋ฆฌ ์ธ์ฌ์ดํธ๋ฅผ ์ ๊ณตํ๋ค.
(i)์ ๊ฒฝ์ฐ, ๋ ์ง์ญ ๊ฐ ์์ ๋ฌด์ญ์ ์ํ ์๋ฐฉํฅ ๋ค ๋จ๊ณ ์ปจํ
์ด๋ ๊ณต๊ธ๋ง์์ ๊ณต ์ปจํ
์ด๋ ๊ด๋ฆฌ ์ ๋ต์ ์ฐ๊ตฌํ๋ค. ์ด ์ ๋ต์ ํ์ ์ผ๋ก ์ธํ ๋์ ํด์ ์ด์ก ๋น์ฉ๊ณผ ๊ธด ๋ฐฐ์ก ์๊ฐ์ ์ค์ผ ์ ์๋ค. ๋ํ, ์งํญ ์์ก์ ์ํฅ์ ์กฐ์ฌํ์ฌ ์ ํ๋ ํญ๊ตฌ ์ค ์ฌ๋ฐฐ์น ํ ๊ณต ์ปจํ
์ด๋ ์, ์๋ ์ปจํ
์ด๋ ์, ๋ ์ง์ญ์ ์์ถ์
์์ ์์
์
์์ ์ โ๊ณต ์ปจํ
์ด๋ ๋ํ ์์๋ฅผ ๋ง์กฑํ๊ธฐ ์ํ ๊ฒฝ๋ก ์ ํ์ ๊ฒฐ์ ํ๊ฒ ๋๋ค. APSO ๋ฐ ํด๋ฆฌ์คํฑ์ ๊ธฐ๋ฐ์ผ๋ก ํ๋ ํ์ด๋ธ๋ฆฌ๋ ํด๋ฒ์ ์ ์ํ๋ฉฐ ๋น๊ต ์คํ์ ํ์๋ค.
(ii)์ ๊ฒฝ์ฐ ์ต์ devanning time ๊ฒฐ์ ์ ๋ชฉํ๋ก ๊ณต ์ปจํ
์ด๋์ ๋ฐํ ์ง์ฐ๊ณผ ํด๋น ์์๋ฃ ๋ถ๊ณผ ๊ฒฐ์ ํ๋ก์ธ์ค์ ๊ด๋ จํ์ฌ ์๋ก ๋ค๋ฅธ ์ธ ๊ฐ์ง ์๋๋ฆฌ์ค๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ์ โ๊ณต ์ปจํ
์ด๋ ๊ณต๊ธ๋ง ๋ชจํ์ ์ ์ํ๋ค. ๊ฐ ์ ํ์ ์ ์ฑ
์ (๋ถ๊ถํ ๋ฐ ์ค์ ์ง์คํ) ํจ๊ณผ๋ ์ ์ ๋ฐํ์จ์ ํฌํจํ ์ฃผ์ ์ฑ๋ฅ ์ธก์ ์ ๊ณ ๋ คํ๋ ๊ณ์ฐ ์คํ์ ํตํด ๊ฒฐ์ ๋๋ค. ์ด๋ฌํ ์ ์ฑ
์คํ์ ๋ํ ์ ์ฉํ ๊ด๋ฆฌ ์ธ์ฌ์ดํธ๋ ๋ฏผ๊ฐ๋ ๋ถ์ ๋ฐ ๋น๊ต ์ฐ๊ตฌ์ ๊ฒฐ๊ณผ์์ ๋์ถํ๋ค.
(iii)์ ๊ฒฝ์ฐ, ๋ณธ ๋
ผ๋ฌธ์ ์ปจํ
์ด๋ ๋คํธ์ํฌ ํ๋ฆ์ ๊ธฐ๋ฐ์ผ๋ก ํ๋ ์ ๋ขฐ์ฑ ๋ชจํ์ ๊ฐ๋ฐํ๋ ๋์์ ์ํฌ ๋ฐ ๋
ธ๋ failure๊ฐ ์์ ๋ street-turn ๋ฐ ๊ณต ์ปจํ
์ด๋ ์ฌ๋ฐฐ์น ๋น์ฉ์ ํฌํจํ ๊ธฐ๋ ์ด ๋น์ฉ์ ๊ตฌํ๋ค. ์ค๋จ์ด ์ปจํ
์ด๋ ๊ณต๊ธ๋ง ๋คํธ์ํฌ์ ๋ฏธ์น๋ ์ํฅ์ ๋ถ์ํ๊ธฐ ์ํด ๋ฏผ๊ฐ๋ ๋ถ์์ ์ํํ์ผ๋ฉฐ disruption ๋น์ฉ์ ๊ฒฐ์ ํ๊ธฐ ์ํด ๋ฒค์น๋งํฌ ๋ชจํ์ ํ์ฉํ๋ค. ๋๋ถ์ด ์ ๋ขฐ์ฑ์ ๊ณ ๋ คํ ์ปจํ
์ด๋ ๋คํธ์ํฌ ํ๋ฆ์ ๊ตฌ์ถํ๊ณ ์ ๋ขฐ์ฑ์ ์ ์งํ๋ ๋ฐฉ๋ฒ์ ๋ํ ๊ด๋ฆฌ์ ์ธ์ฌ์ดํธ๋ ์ ๊ณตํ๋ค.Abstract i
Contents ii
List of Tables vi
List of Figures viii
1. Introduction 1
1.1 Empty Container Repositioning Problem 1
1.2 Reliability Problem 3
1.3 Research Motivation and Contributions 4
1.4 Outline of the Dissertation 7
2. Two-Way Four-Echelon Container Supply Chain 8
2.1 Problem Description and Literature Review 8
2.2 Mathematical Model for the TFESC 15
2.2.1 Overview and Assumptions 15
2.2.2 Notation and Formulation 19
2.3 Solution Procedure for the TFESC 25
2.3.1 Pseudo-Function-based Optimization Problem 25
2.3.2 Objective Function Evaluation 28
2.3.3 Heuristics for Reducing the Number of Leased Containers 32
2.3.4 Accelerated Particle Swarm Optimization 34
2.4 Computational Experiments 37
2.4.1 Heuristic Performances 39
2.4.2 Senstivity Analysis of Varying Periods 42
2.4.3 Senstivity Analysis of Varying Number of Echelons 45
2.5 Summary 48
3. Laden and Empty Container Supply Chain under Decentralized and Centralized Policies 50
3.1 Problem Description and Literature Review 50
3.2 Scenario-based Model for the LESC-DC 57
3.3 Model Development for the LESC-DC 61
3.3.1 Centralized Policy 65
3.3.2 Decentralized Policies (Policies I and II) 67
3.4 Computational Experiments 70
3.4.1 Numerical Exmpale 70
3.4.2 Sensitivity Analysis of Varying Degree of Risk in Container Return 72
3.4.3 Sensitivity Analysis of Increasing L_0 74
3.4.4 Sensitivity Analysis of Increasing t_r 76
3.4.5 Sensitivity Analysis of Decreasing es and Increasing e_f 77
3.4.6 Sensitivity Analysis of Discounting ใpnใ_{f1} and ใpnใ_{f2} 78
3.4.7 Sensitivity Analysis of Different Container Fleet Sizes 79
3.5 Managerial Insights 81
3.6 Summary 83
4. Reliable Container Supply Chain under Disruption 84
4.1 Problem Description and Literature Review 84
4.2 Mathematical Model for the RCNF 90
4.3 Reliability Model under Disruption 95
4.3.1 Designing the Patterns of q and s 95
4.3.2 Objective Function for the RCNF Model 98
4.4 Computational Experiments 103
4.4.1 Sensitivity Analysis of Expected Failure Costs 106
4.4.2 Sensitivity Analysis of Different Network Structures 109
4.4.3 Sensitivity Analysis of Demand-Supply Variation 112
4.4.4 Managerial Insights 115
4.5 Summary 116
5. Conclusions and Future Research 117
Appendices 120
A Proof of Proposition 3.1 121
B Proof of Proposition 3.2 124
C Proof of Proposition 3.3 126
D Sensitivity Analyses for Results 129
E Data for Sensitivity Analyses 142
Bibliography 146
๊ตญ๋ฌธ์ด๋ก 157
๊ฐ์ฌ์ ๊ธ 160Docto
Meta-heuristic based Construction Supply Chain Modelling and Optimization
Driven by the severe competition within the construction industry, the necessity of improving and optimizing the performance of construction supply chain has been aroused. This thesis proposes three problems with regard to the construction supply chain optimization from three perspectives, namely, deterministic single objective optimization, stochastic optimization and multi-objective optimization respectively. Mathematical models for each problem are constructed accordingly and meta-heuristic algorithms are developed and applied for resolving these three problems
A Two-Echelon Location-inventory Model for a Multi-product Donation-demand Driven Industry
This study involves a joint bi-echelon location inventory model for a donation-demand driven industry in which Distribution Centers (DC) and retailers (R) exist. In this model, we confine the variables of interest to include; coverage radius, service level, and multiple products. Each retailer has two classes of product flowing to and from its assigned DC i.e. surpluses and deliveries. The proposed model determines the number of DCs, DC locations, and assignments of retailers to those DCs so that the total annual cost including: facility location costs, transportation costs, and inventory costs are minimized. Due to the complexity of problem, the proposed model structure allows for the relaxation of complicating terms in the objective function and the use of robust branch-and-bound heuristics to solve the non-linear, integer problem. We solve several numerical example problems and evaluate solution performance
Robust optimisation of dry port network design in the container shipping industry under uncertainty
PhD ThesisThe concept of dry port has attracted the attention of many researchers in the field of containerised
transport industry over the past few decades. Previous research on dry port container network
design has dealt with decision-making at different levels in an isolated manner. The purpose of
this research is to develop a decision-making tool based on mathematical programming models to
integrate strategic level decisions with operational level decisions. In this context, the strategic
level decision making comprises the number and location of dry ports, the allocation of customers
demand, and the provision of arcs between dry ports and customers within the network. On the
other hand, the operational level decision making consists of containers flow, the selection of
transportation modes, empty container repositioning, and empty containers inventory control. The
containers flow decision involves the forward and backward flow of both laden and empty
containers. Several mathematical models are developed for the optimal design of dry port networks
while integrating all these decisions.
One of the key aspects that has been incorporated in this study is the inherent uncertainty of
container demands from end customers. Besides, a dynamic setting has to be adopted to consider
the inevitable periodic fluctuation of demands. In order to incorporate the abovementioned
decision-making integration with uncertain demands, several models are developed based on twostage stochastic programming approach. In the developed models, the strategic decisions are made
in the first stage while the second-stage deals with operational decisions. The models are then
solved through a robust sample average approximation approach, which is improved with the
Benders Decomposition method. Moreover, several acceleration algorithms including multi-cut
framework, knapsack inequalities, and Pareto-optimal cut scheme are applied to enhance the
solution computational time.
The proposed models are applied to a hypothetical case of dry port container network design in
North Carolina, USA. Extensive numerical experiments are conducted to validate the dry port
network design models. A large number of problem instances are employed in the numerical
experiments to certify the capability of models. The quality of generated solutions is examined via
a statistical validation procedure. The results reveal that the proposed approach can produce a
reliable dry port container network under uncertain environment. Moreover, the experimental
results underline the sensitivity of the configuration of the network to the inventory holding costs
iii
and the value of coefficients relating to model robustness and solution robustness. In addition, a
number of managerial insights are provided that may be widely used in container shipping
industry: that the optimal number of dry ports is inversely proportional to the empty container
holding costs; that multiple sourcing is preferable when there are high levels of uncertainty; that
rail tends to be better for transporting laden containers directly from seaports to customers with
road being used for empty container repositioning; service level and fill rate improve when the
design targets more robust solutions; and inventory turnover increases with high levels of holding
cost; and inventory turnover decreases with increasing robustness
A hybrid polyhedral uncertainty model for the robust network loading problem
[No abstract available
On distributed virtual network embedding with guarantees
To provide wide-area network services, resources from different infrastructure providers are needed. Leveraging the consensus-based resource allocation literature, we propose a general distributed auction mechanism for the (NP-hard) virtual network (VNET) embedding problem. Under reasonable assumptions on the bidding scheme, the proposed mechanism is proven to converge, and it is shown that the solutions guarantee a worst case efficiency of (?????) relative to the optimal solution, and that this bound is optimal, that is, no better approximation exists. Using extensive simulations, we confirm superior convergence properties and resource utilization when compared with existing distributed VNET embedding solutions, and we show how byappropriate policy design, our mechanism can be instantiated to accommodate the embedding goals of different service and infrastructure providers, resulting in an attractive and flexible resource allocation solution.This work is supported in part by the National Science Foundation under grant CNS-0963974
On distributed virtual network embedding with guarantees
To provide wide-area network services, resources from different infrastructure providers are needed. Leveraging the consensus-based resource allocation literature, we propose a general distributed auction mechanism for the (NP-hard) virtual network (VNET) embedding problem. Under reasonable assumptions on the bidding scheme, the proposed mechanism is proven to converge, and it is shown that the solutions guarantee a worst case efficiency of (?????) relative to the optimal solution, and that this bound is optimal, that is, no better approximation exists. Using extensive simulations, we confirm superior convergence properties and resource utilization when compared with existing distributed VNET embedding solutions, and we show how byappropriate policy design, our mechanism can be instantiated to accommodate the embedding goals of different service and infrastructure providers, resulting in an attractive and flexible resource allocation solution.This work is supported in part by the National Science Foundation under grant CNS-0963974
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