A mathematical optimization model for secondary settler

The study of secondary settler modelling, which aims to establish the main model (one-dimensional-1D model), which is involved in some fundamental processes of the hydrodynamic behaviour of this liquid/solid separation unit and to engender variations of the sludge blanket height as a function of the operating parameters and maintaining of the municipal wastewater treatment plant of Setif. The objective of this research is focused on solid/liquid separation in the secondary settler by attempting a mathematical model that allows us to evaluate the sedimentation velocity as a function of the sludge settleability parameters.

Approach for the Design of Specialized Ships: The Case of Cargo Transport to an Ocean Island

The island of Fernando de Noronha (FN) is a marine protected area, located about 293 nautical miles from Recife, Brazil. Supplies are transported out by improvised boats and the main freight contractor, the Administration of FN (AFN) spends large sums with outsourced shipping services, some of which could be redirected to problems of major concern such as health, environment and education. Using a sequence of five steps, including the construction of a database, mathematical simulation and economic feasibility analysis, it was possible to develop a preliminary design for a specialized economically viable vessel, which meets the requirement, draught limitations and needs of the island of FN. It is shown that the approach is feasible through the construction of a mathematical optimization model and a design of a vessel of about 450 tons of displacement that allows cost savings to AFN of around US$ 1.76M per year.

Textile supply chain management considering carbon emissions and apparel demand fuzziness: a fuzzy mathematical programming approach

PurposeThis paper studies the textile supply chain tactical planning under demand fuzziness through considering environmentally friendly and social responsibility. Hence, carbon emission in textile production and transportation is considered along with supply chain profitability.Design/methodology/approachThe authors present a fuzzy multi-objective mathematical optimization model with credibilistic chance constraints to determine the fabric procurement quantities and production plan under uncertainty. The solution procedure makes use of credibility measure and fuzzy aggregation operator to attain compromise solutions.FindingsA trade-off among carbon emissions, social performance and supply chain total profit is conducted. The analyses indicate the importance of transportation costs and carbon emission while determining the supply chain's tactical plan.Originality/valueThe textile supply chain's social sustainability alongside carbon emissions of textile operations is contemplated to provide apparel production and distribution logistics planning under uncertainty. In doing so, the authors propose a hybrid credibility-possibility mathematical optimization model to determine a compromise solution for textile managers.

Optimization of Mixed Numerology Profiles for 5G Wireless Communication Scenarios

The management of 5G resources is a demanding task, requiring proper planning of operating numerology indexes and spectrum allocation according to current traffic needs. In addition, any reconfigurations to adapt to the current traffic pattern should be minimized to reduce signaling overhead. In this article, the pre-planning of numerology profiles is proposed to address this problem, and a mathematical optimization model for their planning is developed. The idea is to explore requirements and impairments usually present in a given wireless communication scenario to build numerology profiles and then adopt one of the profiles according to the current users/traffic pattern. The model allows the optimization of mixed numerologies in future 5G systems under any wireless communication scenario, with specific service requirements and impairments, and under any traffic scenario. Results show that, depending on the granularity of the profiles, the proposed optimization model is able to provide satisfaction levels of 60–100%, whereas a non-optimized approach provides 40–65%, while minimizing the total number of numerology indexes in operation.

Mathematical model of steel consumption minimization considering the two-stage billets cutting

Purpose. To achieve a decrease in energy and resource costs in the multi-stage production of rolled products within a given plan through the development of appropriate mathware. Methodology. The multi-stage problem mathware for producing rolling steel products is developed on the basis of system approach applying fundamental principles of the optimization and operation research theory. Realization of the developed mathematical model allows discovering such a strategy of using steel during the whole manufacturing process, which minimizes not only the steel waste at the moment of its casting in a mold, but also the offcuts in the process of cutting the obtained ingots into the billets. Findings. A mathematical task model is built to minimize the amount of steel for producing a certain order of size of one cast volume only. The developed model specifies the possibility to pre-evaluate the billet optimal size, based on the necessary cutting along the final product length, appropriate for the certain billet form of section, and ingot weight limits. Originality. A mathematical model is provided for the optimal metal distribution process when implementing the plan of manufacturing rolling products. The model, in contrast to the existing ones, shifts the emphasis on forming the optimal ingot weight, which has a pre-calculated optimal cutting plan. Practical value. The use of the developed mathematical optimization model (minimizing the amount of steel for producing a certain order) as part of an automated decision support system for management of rolling production will reduce the number of cutting machine changeover and minimize resources use and stock balance.

A Mathematical Model for the Optimization of Renewable Energy Systems

The generation of energy from renewable sources is a fundamental aspect for the sustainable development of society, and several energy sources such as solar, biomass, biogas, and wind must be used to the maximum to meet existing needs. In Chile, there are villages that are off-grid. A real case study is presented in this research. To meet the needs of this village we have proposed a mathematical optimization model using a CPLEX optimizer to generate the necessary energy power while minimizing the cost of energy (COE). In this study, different scenarios have been evaluated with respect to the existing energy availabilities, for example, in different periods of the year, demonstrated in terms of economic costs, the viability of resources such as biomass and biogas, and the viability of the energy production of wind power given the associated high costs. Finally, the effect of the use of renewable energy in consideration of CO2 emissions is studied in our research.

Optimal Semi-Competitive Intermediation Networks

In this work we address the problem of optimizing collective profitability in semi-competitive intermediation networks defined as augmented directed acyclic graphs. Network participants are modeled as autonomous agents endowed with private utility functions. We introduce a mathematical optimization model for defining pricing strategies of network participants. We employ welfare economics aiming to maximize the Nash social welfare of the intermediation network. The paper contains mathematical results that theoretically prove the existence of such optimal strategies. We also discuss computational results that we obtained using a nonlinear convex numerical optimization package.

Bus Timetable Design to Ensure Smooth Transfers in Areas with Low-Frequency Public Transportation Services

This study investigates the timetable design problem in areas with low-frequency public transportation services. In Japan, rural areas face sparse populations and rapid growth in the percentage of elderly people. In these areas, many bus lines offer fewer than 10 services per day. In addition to low-frequency services, it is also inconvenient to transfer to another bus or train service. Thus, there is a strong need to design a timetable that ensures smooth transfers among buses and trains. We tackle this problem by adopting existing bus lines and train timetables as much as possible to avoid drastic changes such as an increase in the number of services. Based on this approach, we present a mathematical optimization model to generate a revised bus timetable that shortens waiting time for transfers compared with the current timetable. We apply our model to a part of the Tohoku District in Japan and demonstrate its usefulness in the real world.