Tramp Ship Scheduling Problem with Berth Allocation Considerations and Time-dependent Constraints

This work presents a model for the Tramp Ship Scheduling problem including berth allocation considerations, motivated by a real case of a shipping company. The aim is to determine the travel schedule for each vessel considering multiple docking and multiple time windows at the berths. This work is innovative due to the consideration of both spatial and temporal attributes during the scheduling process. The resulting model is formulated as a mixed-integer linear programming problem, and a heuristic method to deal with multiple vessel schedules is also presented. Numerical experimentation is performed to highlight the benefits of the proposed approach and the applicability of the heuristic. Conclusions and recommendations for further research are provided.Comment: 16 pages, 3 figures, 5 tables, proceedings paper of Mexican International Conference on Artificial Intelligence (MICAI) 201

A genetic algorithm for berth allocation and quay crane assignment

13th Ibero-American Conference on Artificial Intelligence. IBERAMIA 2012, Cartagena de Indias, Colombia. 13-16 November 2012The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-34654-5_61Container terminals are facilities where cargo containers are transshipped between different transport vehicles, for onward transportation. They are open systems that carry out a large number of different combinatorial problems that can be solved by means of Artificial Intelligence techniques. In this work, we focus our attention on scheduling a number of incoming vessels by assigning to each a berthing position, a mooring time and a number of Quay Cranes. This problem is known as the Berthing Allocation and Quay Crane Assignment problem. To formulate the problem, we first propose a mixed integer linear programming model to minimize the total weighted service time of the incoming vessels. Then, a meta-heuristic algorithm (Genetic Algorithm (GA)) is presented for solving the proposed problem. Computational experiments are performed to evaluate the effectiveness and efficiency of the proposed metho

Optical thickness and effective radius of Arctic boundary-layer clouds retrieved from airborne nadir and imaging spectrometry

Arctic boundary-layer clouds in the vicinity of Svalbard (78° N, 15° E) were observed with airborne remote sensing and in situ methods. The cloud optical thickness and the droplet effective radius are retrieved from spectral radiance data from the nadir spot (1.5°, 350–2100 nm) and from a nadir-centred image (40°, 400–1000 nm). Two approaches are used for the nadir retrieval, combining the signal from either two or five wavelengths. Two wavelengths are found to be sufficient for an accurate retrieval of the cloud optical thickness, while the retrieval of droplet effective radius is more sensitive to the number of wavelengths. Even with the comparison to in-situ data, it is not possible to definitely answer the question which method is better. This is due to unavoidable time delays between the in-situ measurements and the remote-sensing observations, and to the scarcity of vertical in-situ profiles within the cloud

Solving Fuzzy Job-Shop Scheduling Problems with a Multiobjective Optimizer

International audienceIn real-world manufacturing environments, it is common to face a job-shop scheduling problem (JSP) with uncertainty. Among different sources of uncertainty, processing times uncertainty is the most common. In this paper, we investigate the use of a multiobjective genetic algorithm to address JSPs with uncertain durations. Uncertain durations in a JSP are expressed by means of triangular fuzzy numbers (TFNs). Instead of using expected values as in other work, we consider all vertices of the TFN representing the overall completion time. As a consequence, the proposed approach tries to obtain a schedule that optimizes the three component scheduling problems (corresponding to the lowest, most probable, and largest durations) all at the same time. In order to verify the quality of solutions found by the proposed approach, an experimental study was carried out across different benchmark instances. In all experiments, comparisons with previous approaches that are based on a single-objective genetic algorithm were also performed

Program trace optimization with constructive heuristics for combinatorial problems

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.EvoCOP: 19th European Conference on Evolutionary Computation in Combinatorial Optimisation, 24-26 April 2019, Leipzig, GermanyProgram Trace Optimisation (PTO), a highly general optimisation framework, is applied to a range of combinatorial optimisation (COP) problems. It effectively combines \smart" problem-specifi c constructive heuristics and problem-agnostic metaheuristic search, automatically and implicitly designing problem-appropriate search operators. A weakness is identifi ed in PTO's operators when applied in conjunction with smart heuristics on COP problems, and an improved method is introduced to address this. To facilitate the comparison of this new method with the original, across problems, a common format for PTO heuristics (known as generators) is demonstrated, mimicking GRASP. This also facilitates comparison of the degree of greediness (the GRASP alpha parameter) in the heuristics. Experiments across problems show that the novel operators consistently outperform the original without any loss of generality or cost in CPU time; hill-climbing is a sufficient metaheuristic; and intermediate levels of greediness are usually best

A new method for deriving aerosol solar radiative forcing and its first application within MILAGRO/INTEX-B

We introduce a method for deriving aerosol spectral radiative forcing along with single scattering albedo, asymmetry parameter, and surface albedo from airborne vertical profile measurements of shortwave spectral irradiance and spectral aerosol optical thickness. The new method complements the traditional, direct measurement of aerosol radiative forcing efficiency from horizontal flight legs below gradients of aerosol optical thickness, and is particularly useful over heterogeneous land surfaces and for homogeneous aerosol layers where the horizontal gradient method is impractical. Using data collected by the Solar Spectral Flux Radiometer (SSFR) and the Ames Airborne Tracking Sunphotometer (AATS-14) during the MILAGRO (Megacity Initiative: Local and Global Research Observations) experiment, we validate an over-ocean spectral aerosol forcing efficiency from the new method by comparing with the traditional method. Retrieved over-land aerosol optical properties are compared with in-situ measurements and AERONET retrievals. The spectral forcing efficiencies over ocean and land are remarkably similar and agree with results from other field experiments

An evolutionary approach to a combined mixed integer programming model of seaside operations as arise in container ports

This paper puts forward an integrated optimisation model that combines three distinct problems, namely berth allocation, quay crane assignment, and quay crane scheduling that arise in container ports. Each one of these problems is difficult to solve in its own right. However, solving them individually leads almost surely to sub-optimal solutions. Hence, it is desirable to solve them in a combined form. The model is of the mixed-integer programming type with the objective being to minimize the tardiness of vessels and reduce the cost of berthing. Experimental results show that relatively small instances of the proposed model can be solved exactly using CPLEX. Large scale instances, however, can only be solved in reasonable times using heuristics. Here, an implementation of the genetic algorithm is considered. The effectiveness of this implementation is tested against CPLEX on small to medium size instances of the combined model. Larger size instances were also solved with the genetic algorithm, showing that this approach is capable of finding the optimal or near optimal solutions in realistic times

Development and Evaluation of an Ethical Guideline for Decisions to Limit Life-Prolonging Treatment in Advanced Cancer: Protocol for a Monocentric Mixed-Method Interventional Study

Background: Many patients with advanced cancer receive chemotherapy close to death and are referred too late to palliative or hospice care, and therefore die under therapy or in intensive care units. Oncologists still have difficulties in involving patients appropriately in decisions about limiting tumor-specific or life-prolonging treatment. Objective: The aim of this Ethics Policy for Advanced Care Planning and Limiting Treatment Study is to develop an ethical guideline for end-of-life decisions and to evaluate the impact of this guideline on clinical practice regarding the following target goals: reduction of decisional conflicts, improvement of documentation transparency and traceability, reduction of distress of the caregiver team, and better knowledge and consideration of patients' preferences. Methods: This is a protocol for a pre-post interventional study that analyzes the clinical practice on treatment limitation before and after the guideline implementation. An embedded researcher design with a mixed-method approach encompassing both qualitative and quantitative methods is used. The study consists of three stages: (1) the preinterventional phase, (2) the intervention (development and implementation of the guideline), and 3) the postinterventional phase (evaluation of the guideline's impact on clinical practice). We evaluate the process of decision-making related to limiting treatment from different perspectives of oncologists, nurses, and patients;comparing them to each other will allow us to develop the guideline based on the interests of all parties. Results: The first preintervention data of the project have already been published, which detailed a qualitative study with oncologists and oncology nurses (n=29), where different approaches to initiation of end-of-life discussions were ethically weighted. A framework for oncologists was elaborated, and the study favored an anticipatory approach of preparing patients for forgoing therapy throughout the course of disease. Another preimplementational study of current decision-making practice (n=567 patients documented) demonstrated that decisions to limit treatment preceded the death of many cancer patients (62/76, 82% of deceased patients). However, such decisions were usually made in the last week of life, which was relatively late. Conclusions: The intervention will be evaluated with respect to the following endpoints: better knowledge and consideration of patients' treatment wishes;reduction of decisional conflicts;improvement of documentation transparency and traceability;and reduction of the psychological and moral distress of a caregiver team

Combined quay crane assignment and quay crane scheduling with crane inter-vessel movement and non-interference constraints

Integrated models of the quay crane assignment problem (QCAP) and the quay crane scheduling problem (QCSP) exist. However, they have shortcomings in that some do not allow movement of quay cranes between vessels, others do not take into account precedence relationships between tasks, and yet others do not avoid interference between quay cranes. Here, an integrated and comprehensive optimization model that combines the two distinct QCAP and QCSP problems which deals with the issues raised is put forward. The model is of the mixed-integer programming type with the objective being to minimize the difference between tardiness cost and earliness income based on finishing time and requested departure time for a vessel. Because of the extent of the model and the potential for even small problems to lead to large instances, exact methods can be prohibitive in computational time. For this reason an adapted genetic algorithm (GA) is implemented to cope with this computational burden. Experimental results obtained with branch-and-cut as implemented in CPLEX and GA for small to large-scale problem instances are presented. The paper also includes a review of the relevant literature