Use Of Linear Programming Research Articles

Bridging Geospatial and Semantic Worlds: Enhancing Analysis of Place-Based Concepts in GIS

People’s actions and behaviours contribute to the diversity and personality of a space, transforming it into a vibrant and thriving living environment. The main goal of this research is to present a GIS-based framework for assessing places. The framework is constructed based on the idea of conceptual spaces, integrating spatial and semantic concepts inside a geometric structure. The explanation of place-related concepts is achieved via the use of linear programming and convex polytopes. By projecting these concepts into the spatial domain, a strong connection between geographical and semantic space is established. This connection allows a wide range of analytical calculations using geographic information systems to be carried out. The study focuses on the sense of city centre in Tehran, Iran, by employing questionnaires administrated on-site to evaluate the correlation between identified city centres and the participants’ responses. The findings demonstrate a good correlation, as shown by a Pearson correlation value of 0.74 and a rank correlation coefficient of 0.8. Interestingly, the city centres that were selected did not always align with the geographic centre. However, participants still perceived them as city centres. This framework serves as a valuable tool for planners and policymakers, providing a comprehensive understanding of the built environment. By considering both semantic and geographical aspects, the framework emphasises the importance of emotions, memories, and meanings in creating an inclusive environment.

Studi Perhitungan Pencampuran Batubara Dengan Pemrograman Linear Untuk Memenuhi Kriteria Permintaan Konsumen Di PT. Alamjaya Bara Pratama Kabupaten Kutai Kartanegara Provinsi Kalimantan Timur

Consumer market demand for certain specifications of coal continues to increase every year. However, each coal company has a variety of coal qualities in terms of calorific value, water content, ash content, and total sulfur and so on. PT. Alamjaya Bara Pratama is a coal mining company that has several types of coal products that vary in quality. By coal blending, the aim is to obtain coal product that meet the target with a homogeneous composition and according to consumer coal quality specifications. With the linear programming method for coal blending calculations using the Production and Operation Management - Quantitave Methods software has an influence in maximizing the use of the composition quantity for each type of product (MD and HS) as well as optimizing the quality of the coal blending results. Through POM-QM, it has the advantage of being able to determine the benchmark target value for one of the desired coal quality parameters. With subbitumious coal quality as for the research results are calculations of the final quality for each Mother Vessel, one of which is MV Eastern Camelia with the planning results is (AC 5,0% adb, TS 0,90% adb, GAR 4590 kcal/kg arb) with tonnage requirements for coal products (MD = 29.727,84 MT and HS = 22.772,16 MT). Through the use of linear programming (POM-QM) in calculating coal blending planning, the results are obtained and meet each coal quality parameter limit criterion based on consumer demand.

Penerapan Program Linear untuk Mengoptimalkan Jumlah Produksi dalam Memperoleh Keuntungan Maksimal pada Rumah UMKM Produk Wedang Sehat

Linear programming is a mathematical method used to solve problems related to linear optimization (maximum value and minimum value). Quoted from Mathematics 3 competency by Johanes, linear programming is a part of mathematics in the form of models, which consist of linear inequalities as a method for solving various problems in everyday life. This linear program can help solve problems ranging from basic to complex. This article aims to apply the use of linear programming in determining the maximum profit that can be obtained for managers of healthy wedang products. In this case, traders of ginger wedang products can use linear programming using the simplex method to find maximum profits manually and analyze using POM-QM for Windows software. The results of the analysis using the linear program of the simplex method with calculations on POM-QM have the same results, namely the maximum profit of MSME houses wedang sehat buk Sumiati in one day reaches Rp. 180,000 by producing healthy wedang ginger powder (X1) as much as 1 piece and wedang sehat suetajarah (X2) as much as 1 piece.

Optimization Model for Selection of the Offshore Fleet Structure

Over the past century, with an accelerated increase in world energy demand, oil remained the most intriguing energy source, while oil exploration and production evolved from an onshore to an offshore exploration and production facility. In logistic and operational planning, the supply of offshore installations is the primary dependent of offshore supply vessels (OSVs). OSVs are classified into two main specialized groups, Anchor Handling Tug Supply (AHTS) and Platform Supply Vessels (PSVs). The establishment and maintenance of offshore oil installations require considerable financial resources for the hire of OSVs, which increases the oil exploration and production operator’s overall budget. Planning the offshore fleet structure aims to reduce expenses and increase the utilization of OSVs. This work will analyze the actual data of the southwestern African offshore market based on 24/7 working time and the use analysis of marine activities to define the parameters of the offshore fleet structure. The research results will be used to develop a methodology for modeling the optimal infrastructure of the offshore fleet. With statistical data of all support vessels’ activities and the use of linear programming (LP), it is possible to determine the vessel’s employment pattern and the optimal fleet structure by type and number of OSVs.

Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis

This study delves into the critical role of logistical cost optimization in the residual woody biomass supply chain, aiming to enhance the sustainability and efficiency of this resource’s exploitation. The research underscores that proficient cost management of logistical operations is pivotal for the economic feasibility of residual biomass utilization. The paper scrutinizes key aspects, such as collection, transportation, storage, and processing of biomass, emphasizing their individual contributions to the overall cost. It also pays particular attention to the impacts of seasonality and biomass quality variations, which directly influence the cost and effectiveness of the supply chain. To facilitate a deeper understanding of these factors, the study introduces mathematical models that enable the exploration of diverse scenarios and optimization strategies. The use of linear programming, genetic algorithms, and tabu search techniques are discussed in the context of these models. The findings of this research hold significant implications for the management of the residual biomass supply chain and contribute to the transition towards a low-carbon economy.

A Study on the Use of Linear Programming in Contract Manufacturing Planning: Example of Automotive Sub-Industry

Bu çalışmada büyük çaplı üretim yapan bir otomotiv yan sanayi işletmesi için kurgulanan matematiksel model üzerinde, işletmenin üretim yapabileceği optimum üretim miktarları ve maksimum kâr hesaplanmaktadır. Yürütülen çalışma ile işletmenin fason üretim ile anlık sipariş artışlarında sipariş karşılayabilme kapasitesinin yükselmesi ve kâr artışı sağlanması amaçlanmaktadır. Çalışmada doğrusal programlama yönteminden faydalanılmış ve hali hazırda yapılan üretime ait veriler ve üretim kısıtları dikkate alınarak fason üretim planlaması için model geliştirilmiştir. İşletmenin kullanmakta olduğu HarmonyERP adlı kurumsal kaynak planlama (KKP) sisteminden alınan 1-Temmuz ile 1-Ağustos 2022 tarih aralığındaki üretim verileri kullanılmıştır. Ürünler için gerekli depolarda kapasite artırımı yapıldığında kâr artışı sağlanmış ve bu kârdan fason üretim maliyeti çıkarıldığında maksimum kâr artışı sağlanabileceği görülmüştür. Çalışma ile işletme üretim kısıtlarına göre en yüksek kârlılığı sağlayacak maksimum üretim adetleri bulunmuş ve fason üretim yaptırılan ürün grubu için üretim planlama yapılmıştır. İşletmenin depo kısıtları da eklenerek fason üretim planlaması için kârın maksimum olacağı seviye bulunmuş ve bu kârlılık seviyesine ulaşılabilmesi için yakalanması gereken üretim adetleri elde edilmiştir.

An Optimization Technique for Ranch Management

Water is a scarce resource; it is a vital resource in the production of crops for livestock that will directly impact supply chain costs. Many costs occur in poorly deployed irrigation systems that don’t fully utilize land potential, thereby, not produce the proper yield of crops for livestock. An irrigation system can not only reduce initial set up and maintenance costs but reduces land waste while increasing yield of dry matter feed. This research presents a cost benefit analysis approach to determine the practicability of installing an irrigation system onto 54 acres of ranch land by employing the use of linear programming. Specifically, by examining factors that impact costs and production, a generalized model was developed to better understand how this system works on any ranch. These results indicate by optimizing land to its fullest capacity for dry matter, one can then maximize profits generated. This research found the profitability of employing an irrigation system is beneficial even at lower production yields when compared to land with no irrigation system.

Fifty years of operational research in forestry

AbstractThis paper describes operational research (OR) contributions in forestry over the past 50 years, based on scientific pathways along which the authors have traveled. We draw on our personal experiences and recall how the use of OR in forestry has evolved from the early use of linear programming in the Canadian forest products industry in the 1950s and strategic forest management planning by the U.S. Forest Service in the 1960s. We describe the widespread use of OR in many aspects of forestry over a 50‐year timespan (1970–2020) and to the present day, where climate change and biodiversity challenges and increased data availability are important. The paper covers many areas of forestry, including forest management, natural disturbance processes, tactical and operational harvesting, transportation, and value chain management. Each section in the paper includes a historical description of OR‐based key applications as well as OR‐based model and method developments Additionally, we discuss our perceptions of OR in future use and its importance in forestry.

Scoring from pairwise winning indices

The pairwise winning indices, computed in the Stochastic Multicriteria Acceptability Analysis, give the probability with which an alternative is preferred to another. They are computed taking into account all the instances of the assumed preference model compatible with the preference information provided by the Decision Maker mainly, but not exclusively, in terms of pairwise preference comparisons of reference alternatives. In this paper we present a new scoring method assigning a value to each alternative summarizing the results of the pairwise winning indices. Several procedures of this type have been provided in literature. However, our method, expressing the score in terms of a representative additive value function, permits to disaggregate the overall evaluation of each alternative in the sum of contributions of considered criteria. This permits not only to rank the alternatives but also to explain the reasons for which an alternative obtains its evaluation and, consequently, fills a certain ranking position. We also present a probabilistic model underlying our methodology. This probabilistic model is based on a simple piecewise linear approximation of the cumulative normal distribution, which allows the use of linear programming. To prove the efficiency of the method in representing the preferences of the Decision Maker, we performed an extensive set of simulations varying the number of alternatives and criteria. The results of the simulations, analyzed from a statistical point of view, prove the reliability of our procedure. The applicability of the method to decision making problems is explained by means of a case study related to the evaluation of financial funds.

Efficient Temporal Piecewise-Linear Numeric Planning With Lazy Consistency Checking

Temporal planning often involves numeric effects that are directly proportional to their action's duration. These include continuous effects, where a numeric variable is subjected to a rate of change while the action is being executed, and discrete duration-dependent effects, where the variable is updated instantaneously but the magnitude of such change is computed from the action's duration. When these effects are linear, state--of--the--art temporal planners often make use of Linear Programming to ensure that these numeric updates are consistent with the chosen start times and durations of the plan's actions. This is typically done for each evaluated state as part of the search process. This exhaustive approach is not scalable to solve real-world problems that require long plans, because the linear program's size becomes larger and slower to solve. In this work we propose techniques that minimise this overhead by computing these checks more selectively and formulating linear programs that have a smaller footprint. The effectiveness of these techniques is demonstrated on domains that use a mix of discrete and continuous effects, which is typical of real-world planning problems. The resultant planner also outperforms most state-of-the-art temporal-numeric and hybrid planners, in terms of both coverage and scalability.

Edukasi: Optimasi Menggunakan Metode Simpleks Pada Usaha Bahan Bakar Minyak Berskala Kecil

The COVID-19 pandemic has forced small-scale businesses to innovate. One of them is a business owned by Mr. Ruddy which sells gasoline and pertalite types of fuel oil. Before the pandemic hit, this business could be said to be running smoothly, but during the pandemic this business began to be deserted from consumers. During the pandemic, the Sorong city government implemented regulations related to PPKM. This regulation also contributes to the reduction of consumers for Mr. Ruddy's business, because people are limited in their mobility. Seeing the situation experienced by Mr. Ruddy's business, the PkM team of the Information Systems Study Program at Victory Sorong University offers an educational program on the use of Linear Programs by utilizing the Simplex method and information technology in the form of POM-QM software for windows version 5.3. The purpose of this educational program is to share knowledge to help small-scale businesses, especially Mr. Ruddy's businesses, to continue to innovate and survive during the pandemic. Where Mr. Ruddy can gain knowledge that can be used for decision making in business operations.

A study of linear programming technique

This paper focuses on one of the most used techniques of operations research i.e. linear programming. The linear programming is a mathematical method to provide an optimal solution for the problems where objective and the requirements both are linear. The limelight during the Second World War The rapid use of linear programming in various fields started after the Second World War. This study provides insights on the assumptions and properties of the linear programming. It also explains the process of formulating any problem as a linear programming problem if all the assumptions are satisfied. The limitations and mathematical formulation are also problem if all the assumptions are satisfied. The limitations and mathematical formulation are also explained. Some practical applications of linear programming are discussed. This study also provides insight on the latest applications of linear programming problem in various fields like sports, lean manufacturing, financial planning and radiotherapy.

Application of Matrices and Linear Programming in Economics

Matrix play an important role in analyzing most complex problems for instance, it is used to find the production level in describing the quantum mechanics of atomic structure, relationship and even used in plotting complicated dance steps. Similarly, it is used to keep track of coefficient of linear transformation structure of complicated systems and also used to describe linear equation. However, making use of the simplex method makes the optimization problem very easy to interpret. Matrix theory is a branch of mathematics which enables the use of linear programming to obtain solutions to problem in the economics sector. The use of the simplex method makes it easier in economics computation where cost and profits can be calculated. The objectives of this study are to investigate the application matrices and linear programming in economics and to reveal the techniques of applying matrix in solving economics problems. The use of matrix in various field of study especially economic is very necessary. The simplex method which is now on interactive computation procedure has more advantage over other matrix methods such that, it can be used to solve linear optimization problems whose constraints are inequalities while Crammer’s rule and Jacobian’s method are used in solving systems of linear equations. This study reported that the use of the simplex method makes it easier to interpret economics and business results earlier. In addition, economists need to make use of matrix in work in the computation of economic theories. The study found that economists could also make use of equation to represent the relationship between economics variables. Graphs are drawn to illustrate the nature of this relationship. The authors also reported that matrixes could be used by economists in solving demand and supply challenges and also through the use of equations to find the equilibrium price of goods. The authors suggested that matrix should be use by the mathematicians to go into the economy of the nation. Keywords: Matrix Theory: Linear Programming: Business Sector: Economics: Simplex Method: Mathematics.

Zonotopic Filtering for Uncertain Nonlinear Systems: Fundamentals, Implementation Aspects, and Extensions [Applications of Control

This tutorial provides a comprehensive perspective on the study of zonotopic filtering for nonlinear uncertain dynamical systems. Unlike stochastic methods that characterize the states by means of random vectors, set-based observers estimate deterministic sets that are guaranteed to contain the system states. Among many classes of sets, the focus here is on zonotopes due to their appealing properties that pursue a good tradeoff between precision and computational cost. We start by reviewing the fundamentals of zonotopic filtering together with illustrative examples. As nonlinear systems bring up many challenges for this topic, we choose one of the first nonlinear zonotopic observers proposed in the literature to guide a series of discussions. After presenting this algorithm and understanding its limitations, we extend it by incorporating state inequality constraints. In addition, we motivate the use of linear programs when solving minimum-volume intersections. Additionally, we give a practical discussion on the implementation of discrete-time zonotopic algorithms for sampled-data nonlinear dynamical systems. To better introduce the zonotopic approaches, we briefly review unscented Kalman filtering to trace parallels between the stochastic and set-theoretic frameworks. Then the presented algorithms are experimented and compared in a case study involving a quadrotor unmanned aerial vehicle.

Investigating the Use of Linear Programming and Evolutionary Algorithms for Multi-Objective Electric Vehicle Charging Problem

With the increasing uptake of electric vehicles (EVs), the need for efficient scheduling of EV charging is increasingly becoming important. A charging station operator needs to identify charging/discharging power of the client EVs over a time horizon while considering multiple objectives, such as operating costs and the peak power drawn from the grid. Evolutionary algorithms (EAs) are a popular choice when faced with problems involving multiple objectives. However, since the objectives and constraints of this problem can be expressed using linear functions, it is also possible to come up with improvised multi-objective formulations which can be solved with exact techniques such as mixed-integer linear programming (MILP). With both approaches having their potential strengths and pitfalls, it is worth investigating their use to inform the algorithmic choices, which the current study aims to address. In doing so, it makes a number of contributions to the topic, including extension of an existing EV charging problem to a multi-objective form; observing some interesting properties of the problem to improve both the MILP and EA solution approaches; and comparing the performance of MILP and EA. The study provides some useful insights into the problem, initial results and quantitative basis for selecting solution approaches, and highlights some areas of further development.

The ethical shortlisting problem

Hiring is a fundamental, frequent activity for all organizations. Hiring decisions have been reported to be subject to conscious and unconscious biases in the literature. The field of Computational Ethics aims to quantify and maximize the ethicality of decisions. This paper attempts to apply Computational Ethics to the shortlisting process in hiring through the use of Linear Programming. Given a set of applicants for a job with numerical qualification values, the author aims to determine weights for each qualification type to compute scores and resulting rankings for each applicant. To this end, Abstract Moral Theories of Utilitarianism, Maximin/Leximin, Egalitarianism, and Prioritarianism are utilized and applied to a set of randomly generated applicant data. Computational experiments demonstrate that the models are scalable and return interpretable results. The necessity of a quota-based shortlisting system to alleviate disadvantaged candidates is highlighted. The author recommends the use of the Maximin model and iteratively eliminating the applicant with the lowest score.

The use of linear programming to determine whether breastfed infants can achieve a nutritionally adequate complementary feeding diet: a case study of 6–11-month-old infants from KwaMashu, KwaZulu-Natal, South Africa

Objectives: The objectives of this study were to ascertain whether the nutrient requirements of 6–11-month-old infants can be met with a food-based approach, and to identify the nutrients of which it is difficult to achieve adequate intakes. Design, setting and subjects: A cross-sectional survey and interviews with mothers and caregivers from the KwaMashu Community Health Centre were conducted. One hundred and thirty-four interviews were completed. This information provided the food consumption input for the model using Optifood software. Results: The results revealed that with the current food pattern of infants from the study group in KwaMashu, iron, zinc and calcium are nutrients whose requirements are likely not to be met in the diet. The percentage RNI (recommended nutrient intake) for iron was 25.2%, zinc 51.3% and calcium 77%. Nutrient intakes for these nutrients of concern improved in the ‘No pattern’ diet but iron and zinc intakes remained below the RNI. According to the best diets modelled by Optifood, it appears that infants in KwaMashu would be able to achieve the recommended intakes of energy, protein, and 8 of the 11 micronutrients, as long as breastfeeding on demand continues during the complementary feeding phase. Conclusions: This study calls into question the continued food-based focus to ensure nutrient adequacy in infants. In conjunction with efforts to improve household food security and continued support and promotion of breastfeeding for the first 2 years of life, targeted micronutrient supplementation may be needed to ensure the optimal growth and development of infants in South Africa.

Mixed‐integer linear programming optimization for the Supply Chain Game

AbstractIn this article, we describe the use of linear programming in conjunction with an online simulation game in an undergraduate supply chain management class. Supply chain management is a required course for students enrolled in a Business Administration program with a concentration in management. It delivers a broad overview of the supply chain management discipline, using a simulation game by Responsive Learning Technologies to provide students with hands‐on experience designing and managing a supply chain. In this teaching brief, I give an overview of the game and present the formulation of an accompanying mixed‐integer linear programming model to design an optimal supply chain that meets customers, demand while maximizing company profit. Students use a spreadsheet template to develop their own implementation of the model and then apply the optimal solution during the simulation. Consequently, they gain an understanding of the role of network optimization in supply chain management. I conclude with recommendations for management of game activities using this model and a brief discussion of some of the issues to be monitored as the game is played.

Use of Linear Programming to Develop Complementary Feeding Recommendations to Improve Nutrient Adequacy and Dietary Diversity Among Breastfed Children in the Rural Philippines.

Lack of dietary diversity in complementary feeding contributes to nutrient gaps leading to undernutrition. Food-based strategies have been successfully used to enrich the complementary diets of infants and young children. However, context-specific recommendations based on an objective diet optimization are needed to formulate sound and practical nutritional guidelines. The present study aimed to identify problem nutrients in complementary diets and formulate complementary feeding recommendations (CFRs) using linear programming analysis for children aged 6 to 23 months in the rural Philippines. A cross-sectional survey was conducted in the municipality of Mercedes, Philippines. Dietary intakes of breastfed children 6 to 8, 9 to 11, and 12 to 23 months of age (n = 297) were assessed using a multipass 24-hour recall method with 7-day food consumption frequency. A linear programming tool was used to identify the recommended nutrient intakes that could not be met within the existing local food patterns and develop CFRs that would best fulfill nutrient adequacy for 11 modeled micronutrients. Problem nutrients in the current diets were iron and calcium in any age-group, zinc for 6 to 8 and 9 to 11 months old, and thiamine and folate for 12 to 23 months old children. Adoption of CFRs with 4 to 5 food groups in the diet would ensure the adequacy of 7 to 8 nutrients, depending on the age-group. Within the boundaries of local dietary patterns, adequacy for most nutrients could be achieved by promoting realistic servings of nutrient-dense foods and food groups. The linear programming results provide an evidence-based strategy in designing interventions to improve the quality of Filipino complementary diets.

Profit Maximization of Magdalena Dairy Raisers Association’s Dairy Products in Magdalena, Laguna

This research demonstrates the use of linear programming in maximizing the profit. It applies the concept of simplex method; a method in linear programming to solve industrial problems that aims to maximize the profit. The Magdalena Dairy Raisers Association specializes in production of dairy products. Three different varieties of dairy products were observed. The data was simulated using MATLAB; a fourth-generation programming language and numerical analysis environment that creates data visualization and user interfaces (UI), calculates matrices, and develops and runs algorithms. The results show that using the Linear Programming Model, we obtain the total revenue of each dairy product with an increase of 108.17% for Fresh Milk, 12.10% for Choco Milk, and 35.95% for Milk O Jel from their previous revenue. As a result, we achieved our goal to maximize the net profit with a total increase of 151.16%..