Multi-agent system with iterative auction mechanism for master bay plan problem in marine logistics

The support of containerization to trade development demands an efficient solution method for the container loading problem in order to reduce shipment and handling time. Hence, the stowage planning of containers is critical to provide speedy delivery of resources from the area of supply to the area of demand. Moreover, information on container terminal activities, structure of ship, and characteristics of containers is distributed among stowage planners. This information imposes constraints, and so the master bay plan problem (MBPP) becomes NP-hard. Therefore, a multi-agent systems (MAS) methodology is designed to effectively communicate the information and solve the MBPP sustainably. In the designed MAS methodology, an information exchange system (IES) is created for stowage planners to bid for ship slots in each experimental iterative combinatorial auction (ICA) market. The winner in the ICA experiments is provided with the ship slots, and the entire bay plan is prepared. Further, the ship-turnaround time is validated using the data obtained from the benchmark problem

Artificial intelligence applications in space and SDI: A survey

The purpose of this paper is to survey existing and planned Artificial Intelligence (AI) applications to show that they are sufficiently advanced for 32 percent of all space applications and SDI (Space Defense Initiative) software to be AI-based software. To best define the needs that AI can fill in space and SDI programs, this paper enumerates primary areas of research and lists generic application areas. Current and planned NASA and military space projects in AI will be reviewed. This review will be largely in the selected area of expert systems. Finally, direct applications of AI to SDI will be treated. The conclusion covers the importance of AI to space and SDI applications, and conversely, their importance to AI

해운물류에서의 접이식 컨테이너 효과 분석

학위논문(박사) -- 서울대학교대학원 : 공과대학 산업공학과, 2022.2. 문일경.컨테이너 화 이후로 해상 물류는 폭발적으로 증가하였고 세계화와 산업 발전을 선도하였다. 하지만 무역량의 증가와 비례하여 수출입 불균형으로 인한 컨테이너의 불균형 문제도 심화되었다. 이러한 문제를 해결하기 위해 다양한 연구자들의 노력이 있었고, 그 중 접이식 컨테이너라는 새로운 개념의 컨테이너가 개발되었다. 하지만 아직 접이식 컨테이너는 상용화 초기 단계이며, 이를 활용한 여러 효과에 대한 연구는 부족한 실정이다. 본 논문에서는 접이식 컨테이너가 도입되었을 때 미칠 수 있는 영향과 그 효과에 대해 다루었다. 먼저 접이식 컨테이너가 크레인 활동에 미치는 영향을 분석하고, 전역적 관점으로 크레인 활동을 줄일 수 있는 방법에 대해 분석하였다. 두 번째로 육상에서의 접이식 컨테이너 적용이 해상과는 다르다는 점에 주목하여 그 효과를 분석하였다. 마지막으로 2008 금융위기와 COVID-19 이후에 증가하고 있는 해운물류의 각종 변동하는 상황 하에서의 접이식 컨테이너 효과에 대해 새로운 통찰을 제공하였다. 1장에서는 간단하게 컨테이너화와 접이식 컨테이너에 대해 설명하고 문제를 주목하게 된 이유와 그 성과를 서술하였다. 2장에서는 접이식 컨테이너가 도입됨에 따라 생길 수 있는 ‘상단 적재 규칙’이 적용되었을 때의 크레인 활동의 변화를 살펴보고 전역적 최적화가 지역적 최적화보다 효과적임을 보였다. 더불어 전역적 최적화를 도입하였을 때 직면할 수 있는 비용 분배 문제에 대해서도 조망하여 그 해결책을 제시하였다. 3장에서는 육상에서 접이식 컨테이너가 수송공간을 줄여주는 장점 외에 경로를 바꾸는 효과가 존재함을 보이고, 다양한 시나리오와 정책에 따라 그 효과가 어떻게 변화하는지에 대해 분석하였다. 4장에서는 증가하는 다양한 변동상황 각각에 대해 접이식 컨테이너의 효과에 대해 분석하였다. 이를 토대로 각 상황에 맞는 최적 접이식 컨테이너 개수를 도출하고 임대 정책을 통해 대응할 수 있다는 통찰을 도출하였다. 5장에서는 본 논문의 결론과 향후 연구 방안에 대해 서술하였다. 본 논문에서 제안하는 문제와 그 해결 방법은 학술적 및 산업적으로 의미가 있다. 학계에는 실제 존재하는 현장의 문제들을 제시하고 문제를 효과적으로 해결할 수 있는 방법들을 제안한다. 산업계에는 신기술인 접이식 컨테이너의 도입에 따라 발생할 수 있는 문제에 대해 정량화 및 모형화를 통한 해결방법을 제시한다. 본 논문을 통해 산업의 발전과 학문의 발전이 함께 이루어질 수 있을 것으로 기대한다.After containerization, maritime logistics experienced the substantial growth of trade volumes and led to globalization and industrial development. However, in proportion to the increase in the volume, the degree of container imbalance also intensified due to the disparity between importing and exporting sizes at ports in different continents. A group of researchers is digging into resolving this ongoing challenge, and a new concept of a container, called a foldable container, has been proposed. Nevertheless, foldable containers are still in the early stage of commercialization, and research on the various effects of using foldable containers seems insufficient yet. This dissertation considers the possible effects of the introduction of foldable containers. First, we analyze the effect of foldable containers on crane operation and reduce shifts from a global perspective. Second, the effect of using foldable containers in hinterland areas was analyzed by noting that the application of foldable containers on land was different from that of the sea. Finally, we provided new insights into the foldable container under plausible dynamic situations in the shipping industry during the COVID-19 and logistics that have increased since the 2008 financial crisis. A brief explanation of containerization and foldable containers is introduced in Chapter 1, along with the dissertation's motivations, contributions, and outlines. Chapter 2 examines changes in crane operation when the 'top stowing rule' that can be treated with foldable containers is applied and shows that global optimization is more effective than local optimization. In addition, we suggested the cost-sharing method to deal with fairness issues for additional costs between ports when the global optimization method is fully introduced. Chapter 3 shows that foldable containers in the hinterland have the effect of changing routes in addition to reducing transportation space and analyzes how the results change according to various scenarios and policies. Chapter 4 analyzes the effectiveness of foldable containers for different dynamic situations. Moreover, the managerial insight was derived that the optimal number of foldable containers suitable for each situation can be obtained and responded to leasing policies. Chapter 5 describes the conclusions of this dissertation and discusses future research. The problem definition and solution methods proposed in this dissertation can be seen as meaningful in both academic and industrial aspects. For academia, we presented real-world problems in the field and suggested ways to solve problems effectively. For industry, we offered solutions through quantification and modeling for real problems related to foldable containers. We expect that industrial development and academic achievement can be achieved together through this dissertation.Chapter 1 Introduction 1 1.1 Containerization and foldable container 1 1.2 Research motivations and contributions 3 1.3 Outline of the dissertation 6 Chapter 2 Efficient stowage plan with loading and unloading operations for shipping liners using foldable containers and shift cost-sharing 7 2.1 Introduction 7 2.2 Literature review 10 2.3 Problem definition 15 2.4 Mathematical model 19 2.4.1 Mixed-integer programming model 19 2.4.2 Cost-sharing 24 2.5 Computational experiment and analysis 26 2.6 Conclusions 34 Chapter 3 Effects of using foldable containers in hinterland areas 36 3.1 Introduction 36 3.2 Single depot repositioning problem 39 3.2.1 Problem description 40 3.2.2 Mathematical formulation of the single depot repositioning problem 42 3.2.3 Effects of foldable containers 45 3.3 Multi-depot repositioning problem 51 3.4 Computational experiments 56 3.4.1 Experimental design for the SDRP 57 3.4.2 Experimental results for the SDRP 58 3.4.3 Major and minor effects with the single depot repositioning problem 60 3.5 Conclusions 65 Chapter 4 Effect of foldable containers in dynamic situation 66 4.1 Introduction 66 4.2 Problem description 70 4.3 Mathematical model 73 4.4 Computational experiments 77 4.4.1 Overview 77 4.4.2 Experiment results 79 4.5 Conclusions 88 Chapter 5 Conclusion and future research 90 Bibliography 94 국문초록 99박

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

A decomposition method for finding optimal container stowage plans

In transportation of goods in large container ships, shipping industries need to minimize the time spent at ports to load/unload containers. An optimal stowage of containers on board minimizes unnecessary unloading/reloading movements, while satisfying many operational constraints. We address the basic container stowage planning problem (CSPP). Different heuristics and formulations have been proposed for the CSPP, but finding an optimal stowage plan remains an open problem even for small-sized instances. We introduce a novel formulation that decomposes CSPPs into two sets of decision variables: the first defining how single container stacks evolve over time and the second modeling port-dependent constraints. Its linear relaxation is solved through stabilized column generation and with different heuristic and exact pricing algorithms. The lower bound achieved is then used to find an optimal stowage plan by solving a mixed-integer programming model. The proposed solution method outperforms the methods from the literature and can solve to optimality instances with up to 10 ports and 5,000 containers in a few minutes of computing time