The Floating-Cuts model: a general and flexible mixed-integer programming model for non-guillotine and guillotine rectangular cutting problems

Two new continuous-time MILP (Mixed Integer Linear Programming) models are developed for resource constrained project scheduling problems in which activities can be conducted in different (multi) modes. There are efficient and flexible MILP models for this problem in which time is represented by a number of discrete time intervals. However, they require to use large numbers of binary variables as the number of activities increases and time horizon stretches. Hence efforts have been made to formulate MILP models based on continuous-time representation and therefore to speed up the solution process. We propose two novel MILP models based on the event and resource flow concepts. The models are verified by solving benchmark problems in the literature.

This study aims to propose an original and flexible integrated mixed integer linear programming (MILP) model for scheduling jobs and crews with job earliness and tardiness, employee workload balancing, relationships between jobs, and multi-skilled crews. The objective is to minimize the total costs related to assigning jobs to crews, job earliness and tardiness, and employee workload heterogeneity.

A new MILP model and fast heuristics for the variable-sized bin packing problem with time windows

Electricity is becoming one of the main forms of the final energy demand in the world; therefore, energy transition is one of the most important issues to achieve the internationally agreed target to limit global warming below 2 °C. This work addressed the optimal mix of renewable energy technologies to substitute any existing power system. A flexible multiobjective mixed-integer linear programming model was developed that can be adapted to any national power system. The proposed optimization framework considers simultaneously technical operating constraints, availability of renewable energy sources in different places, freshwater consumption as a function of technologies and location characteristics, direct and lifecycle greenhouse gas emissions, and total annual costs. The peninsular electricity system (PES) of Spain was chosen to show the applicability of the model due to the imminent decommission of its coal and nuclear thermal plants and its ambitious CO₂ reduction targets. Results show the location, type, capacity, and generation structure of the optimal energy mix with existing and new power plants. The proposed energy transition shows a potential reduction of up to 37.5 and 49.7% in water consumption and greenhouse gas emission, respectively, with respect to the current system.

New and improved level heuristics for the rectangular strip packing and variable-sized bin packing problems

The definition and function of inventory management reveal the importance of modern industry in formulating policies that regulate the supply of raw materials, semi-finished products, and finished products. Unfortunately, most companies fail to consider the characteristics of their raw materials when determining inventory strategies. Raw materials that are perishable are those that consider their service life and storage time. Inventory management plays a crucial role in supply chain management, especially for perishable raw materials, such as food products. PT X, a food business in Padang, experienced difficulty in meeting the demand for rendang products due to a lack of raw materials. Therefore, this study aims to develop an inventory management model that takes into account the perishable raw materials' expiration time. The model development consists of three stages: model development design, inventory model formulation, and model testing. The proposed model resulted in a storage time interval of five days and an optimal order quantity of 34 kg of meat with a safety stock of 14 kg. Implementing this model led to lower total inventory costs for PT X than the actual conditions of the company. The total inventory cost obtained using this model is Rp279,797,822. This study emphasizes the importance of considering the characteristics of raw materials in determining inventory strategies to optimize inventory management effectively and efficiently. The study's findings can serve as a reference for other food businesses encountering similar inventory management challenges in the perishable food industry.

Large-scale feed factories may have multiple production and storage facilities. Any production facility uses its own available raw materials while performing feed formulation. However, ensuring a reasonable cost is achieved, and the desired quality criteria are met, may require obtaining a certain amount of raw material from other facilities. Selecting a specific amount of raw materials among many raw materials in different facilities requires many combinations to be tried out. Providing solutions, especially when there is a large amount of the raw material, may be costly and take more time. A new mixed-integer linear programming (MILP) model that specifies the type of material and the amount of the material to be selected from external facilities has been proposed in this study. When deterministic methods like MILP are used, only one solution result is obtained. However, when the decision-maker would like to see alternative results, solution constraints can be mitigated and a solution provided within the same or similar time. A new method named hybrid-linear binary PSO (H-LBP) has been proposed in this study for the problems that the decision-maker had limited time for and for which the solution results were required in a shorter time. Continuous particle swarm optimization, which works as a hybrid with linear programming, has been used in this method. The new model proposed in this study was tested on the mixed feeds for sheep, cattle and rabbit species by using both MILP and the proposed H-LBP methods. Raw materials determined by the model were added to the mixture, and the cost in each of the three species was observed to go down. In addition, different alternative solutions at reasonable cost and similar quality were presented to the producer/decision-maker in a shorter time.

Bioethanol is one of renewable energy considered as fuel petroleum substitute. Generally, bioethanol can be obtained from raw material which contain of sugar, starch or lignocelluloses, i.e sorghum. The aim of this study was to obtain the optimum condition of NaOH concentration and cellulase:xylanase enzymes for bioethanol production from sweet sorghum bagasse. Raw material used was sweet sorghum bagasse. The experiment was conducted four stages: 1) characteristics of raw materials; 2) optimization effect of NaOH solution on delignification process, experimental design at this stage was completely randomized design (CRD) with 1 factor; 3) optimization effect of cellulase and xylanase enzymes (1:1% and (2:2%) to bioethanol production on scale of 500 g raw materials, statistical analysis that used in this stage was t-student test; 4) optimization process of bioethanol production on scale of 50 kg raw material. The results showed that the optimum condition to produced bioethanol from sweet sorghum bagasse was addition of 10% NaOH solution at a temperature of 120-130 0C for 20 minutes. Furthermore, the resulted material from delignification was proceesed to saccharification and hydrolysis using xylanase: cellulase with ratio of 1:1. The bioethanol produced was 13.7% from total sweet sorghum bagasse powder used with alcohol content of 82.8%.

Aggregating classifiers with mathematical programming

We propose a new static high-performance mesh data structure for triangle surface meshes on the GPU. Our data structure is carefully designed for parallel execution while capturing mesh locality and confining data access, as much as possible, within the GPU's fast "shared memory." We achieve this by subdividing the mesh into patches and representing these patches compactly using a matrix-based representation. Our patching technique is decorated with ribbons , thin mesh strips around patches that eliminate the need to communicate between different computation thread blocks, resulting in consistent high throughput. We call our data structure RXMesh : Ribbon-matriX Mesh. We hide the complexity of our data structure behind a flexible but powerful programming model that helps deliver high performance by inducing load balance even in highly irregular input meshes. We show the efficacy of our programming model on common geometry processing applications---mesh smoothing and filtering, geodesic distance, and vertex normal computation. For evaluation, we benchmark our data structure against well-optimized GPU and (single and multi-core) CPU data structures and show significant speedups.

The new video coding standard: High Efficiency Video Coding (HEVC)/H265 developed by ISO-IEC/MPEG and ITU-T/VCEG, has a goal to improve compression performance over the current H264/MPEG-4 standard, in the range of 50% bit-rate reduction for equal perceptual video quality. However the complexity of the algorithm and data structure of H265 is much higher than H264, that means H265 based codec will require more computing resource/power than its predecessor. In this paper we investigate the HEVC codec characters, focus on CPU based software video trans-coding technologies that provides the best video quality and most flexible programming model, maximize x86 platform capabilities at one HEVC codec, to achieve real-time performance for HEVC encoding codec on x86 platform.

The Pirro Nord site (Apricena, Fg, Southern Italy) in the context of the first European peopling: Convergences and divergences

This paper presents and illustrates an original application of the redesign in the real context of a mining supply chain producing phosphate rock. One of the major challenges is to successfully produce the final products required by the customers, from raw materials whose chemical composition and availability depend on the extraction program and method. Redesign of the mining supply chain consists of considering the impact of extraction, processing, and blending stages in achieving target objectives. The proposed approach, based on a mixed integer linear programming model, allows moving from fixed production flows to dynamic ones by adopting a flexible and reactive management mode that fully satisfies customer requirements at minimum production costs. Numerical results obtained using real data, corresponding to the infrastructure and order books, illustrate (i) the flexibility, quality, and horizontal alignment ensured by our approach and (ii) the impact of the extraction method on the ability of the SC to fulfil the orders book with more efficiency.

This paper analyzes general parallel programming models and identifies the general parallel programming models stack used for high-performance numerical simulation. Then, on the basis of this analysis, domain-specific parallel programming models are presented and their main constitution, including data structures, computational patterns, component models, and programming frameworks, discussed. The inherent relationship among these elements is also analyzed. The J Adaptive Structured Mesh application INfrastructure (JASMIN) framework is used to verify and validate the possibility and effectiveness of these models. Domain-specific parallel programming models will significantly improve the development efficiency of parallel application software.

Two different concepts are introduced and compared to measure for the first time residual absorption in pure and doped fused silica fiber preform raw materials at 940 nm and 1550nm directly by means of the laser induced deflection (LID) technique in order to analyze the minimal achievable attenuation in high power fiber lasers based on the doped fused silica raw materials. It is found, that attaching a thin disk sample of the preform raw material to a practically non-absorbing substrate at the wavelength of investigation is the best measurement concept with respect to material consumption, absolute calibration and impact of the strong scattering in the doped raw materials on the measurement. For several Yb doped laser active raw materials the initial absorption value at 1550 nm (ranging from less than 50 dB/km to about 1800 dB/km) is compared to the total loss achieved for the manufactured fiber at 1200 nm, 1315 nm and 1600 nm, respectively. For some of the chosen materials the fiber loss is very comparable to residual raw material absorption indicating that the initial absorption is the dominant loss mechanism in the manufactured fiber. In contrast, for some fibers the total loss exceeds the values of the raw material absorption which allows the conclusion that additional loss mechanism like scattering, stress, geometrically fluctuation and micro or macro bending contributes to the fiber attenuation.