Analyzing Carbon Trade Permits in Optimization Framework

The threats caused by global warming motivate different stake holders to deal with and control them. This Master's thesis focuses on analyzing carbon trade permits in optimization framework. The studied model determines optimal emission and uncertainty levels which minimize the total cost. Research questions are formulated and answered by using different optimization tools. The model is developed and calibrated by using available consistent data in the area of carbon emission technology and control. Data and some basic modeling assumptions were extracted from reports and existing literatures. The data collected from the countries in the Kyoto treaty are used to estimate the cost functions. Theory and methods of constrained optimization are briefly presented. A two-level optimization problem (individual and between the parties) is analyzed by using several optimization methods. The combined cost optimization between the parties leads into multivariate model and calls for advanced techniques. Lagrangian, Sequential Quadratic Programming and Differential Evolution (DE) algorithm are referred to. The role of inherent measurement uncertainty in the monitoring of emissions is discussed. We briefly investigate an approach where emission uncertainty would be described in stochastic framework. MATLAB software has been used to provide visualizations including the relationship between decision variables and objective function values. Interpretations in the context of carbon trading were briefly presented. Suggestions for future work are given in stochastic modeling, emission trading and coupled analysis of energy prices and carbon permits.

Smooth height/age curves from stem analysis with linear programming

[Abstract]

Using software metrics to increase efficiency in product creation

Opinnäytetyö etsii korrelaatiota ohjelmistomittauksella saavutettujen tulosten ja ohjelmasta löytyneiden virheiden väliltä. Työssä käytetään koeryhmänä jo olemassaolevia ohjelmistoja. Työ tutkii olisiko ohjelmistomittareita käyttämällä ollut mahdollista paikallistaa ohjelmistojen ongelmakohdat ja näin saada arvokasta tietoa ohjelmistokehitykseen. Mittausta voitaisiin käyttää resurssien parempaan kohdentamiseen koodikatselmuksissa, koodi-integraatiossa, systeemitestauksessa ja aikataulutuksessa. Mittaamisen avulla nämä tehtävät saisivat enemmän tietoa resurssien kohdistamiseen. Koeryhmänä käytetään erilaisia ohjelmistotuotteita. Yhteistä näille kaikille tuotteille on niiden peräkkäiset julkaisut. Uutta julkaisua tehtäessä, edellistä julkaisua käytetään pohjana, jonka päällekehitetään uutta lähdekoodia. Tämän takia ohjelmistomittauksessa pitää pystyä erottelemaan edellisen julkaisun lähdekoodi uudesta lähdekoodista. Työssä käytettävät ohjelmistomittarit ovat yleisiä ja ohjelmistotekniikassalaajasti käytettyjä mittaamaan erilaisia lähdekoodin ominaisuuksia, joiden arvellaan vaikuttavan virhealttiuteen. Tämän työn tarkoitus on tutkia näiden ohjelmistomittareiden käytettävyyttä koeryhmänä toimivissa ohjelmistoympäristöissä. Käytännön osuus työstä onnistui löytämään korrelaation joidenkinohjelmistomittareiden ja virheiden väliltä, samalla kuin toiset ohjelmistomittarit eivät antaneet vakuuttavia tuloksia. Ohjelmistomittareita käyttämällä näyttää olevan mahdollista tunnistaa virhealttiit kohdat ohjelmasta ja siten parantaa ohjelmistokehityksen tehokkuutta. Ohjelmistomittareiden käyttö tuotekehityksessäon perusteltavaa ja niiden avulla mahdollisesti pystyttäisiin vaikuttamaan ohjelmiston laatuun tulevissa julkaisuissa.

Python as a programming language for the introductory programming courses

Tämä kandidaatintyö tutkii tietotekniikan perusopetuksessa keskeisen aiheen,ohjelmoinnin, alkeisopetusta ja siihen liittyviä ongelmia. Työssä perehdytään ohjelmoinnin perusopetusmenetelmiin ja opetuksen lähestymistapoihin, sekä ratkaisuihin, joilla opetusta voidaan tehostaa. Näitä ratkaisuja työssä ovat mm. ohjelmointikielen valinta, käytettävän kehitysympäristön löytäminen sekä kurssia tukevien opetusapuvälineiden etsiminen. Lisäksi kurssin läpivientiin liittyvien toimintojen, kuten harjoitusten ja mahdollisten viikkotehtävien valinta kuuluu osaksitätä työtä. Työ itsessään lähestyy aihetta tutkimalla Pythonin soveltuvuutta ohjelmoinnin alkeisopetukseen mm. vertailemalla sitä muihin olemassa oleviin yleisiin opetuskieliin, kuten C, C++ tai Java. Se tarkastelee kielen hyviä ja huonoja puolia, sekä tutkii, voidaanko Pythonia hyödyntää luontevasti pääasiallisena opetuskielenä. Lisäksi työ perehtyy siihen, mitä kaikkea kurssilla tulisi opettaa, sekä siihen, kuinka kurssin läpivienti olisi tehokkainta toteuttaa ja minkälaiset tekniset puitteet kurssin toteuttamista varten olisi järkevää valita.

Simulation Supported Robot Programming using XML

The main objective of this master's thesis is to study robot programming using simulation software, and also how to embed the simulation software into company's own robot controlling software. The further goal is to study a new communication interface to the assembly line's components -more precisely how to connect the robot cell into this new communication system. Conveyor lines are already available where the conveyors use the new communication standard. The robot cell is not yet capable of communicating with to other devices using the new communication protocols. The main problem among robot manufacturers is that they all have their own communication systems and programming languages. There has not been any common programming language to program all the different robot manufacturers robots, until the RRS (Realistic Robot Simulation) standards were developed. The RRS - II makes it possible to create the robot programs in the simulation software and it gives a common user interface for different robot manufacturers robots. This thesis will present the RRS - II standard and the robot manufacturers situation for the RRS - II support. Thesis presents how the simulation software can be embedded into company's own robot controlling software and also how the robot cell can be connected to the CAMX (Computer Aided Manufacturing using XML) communication system.

Promoting Programming Learning. Engagement, Automatic Assessment with Immediate Feedback in Visualizations

The skill of programming is a key asset for every computer science student. Many studies have shown that this is a hard skill to learn and the outcomes of programming courses have often been substandard. Thus, a range of methods and tools have been developed to assist students’ learning processes. One of the biggest fields in computer science education is the use of visualizations as a learning aid and many visualization based tools have been developed to aid the learning process during last few decades. Studies conducted in this thesis focus on two different visualizationbased tools TRAKLA2 and ViLLE. This thesis includes results from multiple empirical studies about what kind of effects the introduction and usage of these tools have on students’ opinions and performance, and what kind of implications there are from a teacher’s point of view. The results from studies in this thesis show that students preferred to do web-based exercises, and felt that those exercises contributed to their learning. The usage of the tool motivated students to work harder during their course, which was shown in overall course performance and drop-out statistics. We have also shown that visualization-based tools can be used to enhance the learning process, and one of the key factors is the higher and active level of engagement (see. Engagement Taxonomy by Naps et al., 2002). The automatic grading accompanied with immediate feedback helps students to overcome obstacles during the learning process, and to grasp the key element in the learning task. These kinds of tools can help us to cope with the fact that many programming courses are overcrowded with limited teaching resources. These tools allows us to tackle this problem by utilizing automatic assessment in exercises that are most suitable to be done in the web (like tracing and simulation) since its supports students’ independent learning regardless of time and place. In summary, we can use our course’s resources more efficiently to increase the quality of the learning experience of the students and the teaching experience of the teacher, and even increase performance of the students. There are also methodological results from this thesis which contribute to developing insight into the conduct of empirical evaluations of new tools or techniques. When we evaluate a new tool, especially one accompanied with visualization, we need to give a proper introduction to it and to the graphical notation used by tool. The standard procedure should also include capturing the screen with audio to confirm that the participants of the experiment are doing what they are supposed to do. By taken such measures in the study of the learning impact of visualization support for learning, we can avoid drawing false conclusion from our experiments. As computer science educators, we face two important challenges. Firstly, we need to start to deliver the message in our own institution and all over the world about the new – scientifically proven – innovations in teaching like TRAKLA2 and ViLLE. Secondly, we have the relevant experience of conducting teaching related experiment, and thus we can support our colleagues to learn essential know-how of the research based improvement of their teaching. This change can transform academic teaching into publications and by utilizing this approach we can significantly increase the adoption of the new tools and techniques, and overall increase the knowledge of best-practices. In future, we need to combine our forces and tackle these universal and common problems together by creating multi-national and multiinstitutional research projects. We need to create a community and a platform in which we can share these best practices and at the same time conduct multi-national research projects easily.

Early nutritional determinants in cardio-metabolic programming – A prospective randomized controlled dietary intervention study

Western societies have been faced with the fact that overweight, impaired glucose regulation and elevated blood pressure are already prevalent in pediatric populations. This will inevitably mean an increase in later manifestations of cardio-metabolic diseases. The dilemma has been suggested to stem from fetal life and it is surmised that the early nutritional environment plays an important role in the process called programming. The aim of the present study was to characterize early nutritional determinants associating with cardio-metabolic risk factors in fetuses, infants and children. Further, the study was designated to establish whether dietary counseling initiated in early pregnancy can modify this cascade. Healthy mother-child pairs (n=256) participating in a dietary intervention study were followed from early pregnancy to childhood. The intervention included detailed dietary counseling by a nutritionist targeting saturated fat intake in excess of recommendations and fiber consumption below recommendations. Cardio-metabolic programming was studied by characterizing the offspring’s cardio-metabolic risk factors such as over-activation of the autonomic nervous system, elevated blood pressure and adverse metabolic status (e.g. serum high split proinsulin concentration). Fetal cardiac sympathovagal activation was measured during labor. Postnatally, children’s blood pressure was measured at six-month and four-year follow-up visits. Further, infants’ metabolic status was assessed by means of growth and serum biomarkers (32-33 split proinsulin, leptin and adiponectin) at the age of six months. This study proved that fetal cardiac sympathovagal activity was positively associated with maternal pre-pregnancy body mass index indicating adverse cardio-metabolic programming in the offspring. Further, a reduced risk of high split proinsulin in infancy and lower blood pressure in childhood were found in those offspring whose mothers’ weight gain and amount and type of fats in the diet during pregnancy were as recommended. Of note, maternal dietary counseling from early pregnancy onwards could ameliorate the offspring’s metabolic status by reducing the risk of high split proinsulin concentration, although it had no effect on the other cardio-metabolic markers in the offspring. At postnatal period breastfeeding proved to entail benefits in cardio-metabolic programming. Finally, the recommended dietary protein and total fat content in the child’s diet were important nutritional determinants reducing blood pressure at the age of four years. The intrauterine and immediate postnatal period comprise a window of opportunity for interventions aiming to reduce the risk of cardio-metabolic disorders and brings the prospect of achieving health benefits over one generation.

Tool-supported invariant-based programming

The development of correct programs is a core problem in computer science. Although formal verification methods for establishing correctness with mathematical rigor are available, programmers often find these difficult to put into practice. One hurdle is deriving the loop invariants and proving that the code maintains them. So called correct-by-construction methods aim to alleviate this issue by integrating verification into the programming workflow. Invariant-based programming is a practical correct-by-construction method in which the programmer first establishes the invariant structure, and then incrementally extends the program in steps of adding code and proving after each addition that the code is consistent with the invariants. In this way, the program is kept internally consistent throughout its development, and the construction of the correctness arguments (proofs) becomes an integral part of the programming workflow. A characteristic of the approach is that programs are described as invariant diagrams, a graphical notation similar to the state charts familiar to programmers. Invariant-based programming is a new method that has not been evaluated in large scale studies yet. The most important prerequisite for feasibility on a larger scale is a high degree of automation. The goal of the Socos project has been to build tools to assist the construction and verification of programs using the method. This thesis describes the implementation and evaluation of a prototype tool in the context of the Socos project. The tool supports the drawing of the diagrams, automatic derivation and discharging of verification conditions, and interactive proofs. It is used to develop programs that are correct by construction. The tool consists of a diagrammatic environment connected to a verification condition generator and an existing state-of-the-art theorem prover. Its core is a semantics for translating diagrams into verification conditions, which are sent to the underlying theorem prover. We describe a concrete method for 1) deriving sufficient conditions for total correctness of an invariant diagram; 2) sending the conditions to the theorem prover for simplification; and 3) reporting the results of the simplification to the programmer in a way that is consistent with the invariantbased programming workflow and that allows errors in the program specification to be efficiently detected. The tool uses an efficient automatic proof strategy to prove as many conditions as possible automatically and lets the remaining conditions be proved interactively. The tool is based on the verification system PVS and i uses the SMT (Satisfiability Modulo Theories) solver Yices as a catch-all decision procedure. Conditions that were not discharged automatically may be proved interactively using the PVS proof assistant. The programming workflow is very similar to the process by which a mathematical theory is developed inside a computer supported theorem prover environment such as PVS. The programmer reduces a large verification problem with the aid of the tool into a set of smaller problems (lemmas), and he can substantially improve the degree of proof automation by developing specialized background theories and proof strategies to support the specification and verification of a specific class of programs. We demonstrate this workflow by describing in detail the construction of a verified sorting algorithm. Tool-supported verification often has little to no presence in computer science (CS) curricula. Furthermore, program verification is frequently introduced as an advanced and purely theoretical topic that is not connected to the workflow taught in the early and practically oriented programming courses. Our hypothesis is that verification could be introduced early in the CS education, and that verification tools could be used in the classroom to support the teaching of formal methods. A prototype of Socos has been used in a course at Åbo Akademi University targeted at first and second year undergraduate students. We evaluate the use of Socos in the course as part of a case study carried out in 2007.

Teaching mathematics and programming : new approaches with empirical evaluation

Programming and mathematics are core areas of computer science (CS) and consequently also important parts of CS education. Introductory instruction in these two topics is, however, not without problems. Studies show that CS students find programming difficult to learn and that teaching mathematical topics to CS novices is challenging. One reason for the latter is the disconnection between mathematics and programming found in many CS curricula, which results in students not seeing the relevance of the subject for their studies. In addition, reports indicate that students' mathematical capability and maturity levels are dropping. The challenges faced when teaching mathematics and programming at CS departments can also be traced back to gaps in students' prior education. In Finland the high school curriculum does not include CS as a subject; instead, focus is on learning to use the computer and its applications as tools. Similarly, many of the mathematics courses emphasize application of formulas, while logic, formalisms and proofs, which are important in CS, are avoided. Consequently, high school graduates are not well prepared for studies in CS. Motivated by these challenges, the goal of the present work is to describe new approaches to teaching mathematics and programming aimed at addressing these issues: Structured derivations is a logic-based approach to teaching mathematics, where formalisms and justifications are made explicit. The aim is to help students become better at communicating their reasoning using mathematical language and logical notation at the same time as they become more confident with formalisms. The Python programming language was originally designed with education in mind, and has a simple syntax compared to many other popular languages. The aim of using it in instruction is to address algorithms and their implementation in a way that allows focus to be put on learning algorithmic thinking and programming instead of on learning a complex syntax. Invariant based programming is a diagrammatic approach to developing programs that are correct by construction. The approach is based on elementary propositional and predicate logic, and makes explicit the underlying mathematical foundations of programming. The aim is also to show how mathematics in general, and logic in particular, can be used to create better programs.

Enabling constructive alignment in programming instruction

In this thesis, simple methods have been sought to lower the teacher’s threshold to start to apply constructive alignment in instruction. From the phases of the instructional process, aspects that can be improved with little effort by the teacher have been identified. Teachers have been interviewed in order to find out what students actually learn in computer science courses. A quantitative analysis of the structured interviews showed that in addition to subject specific skills and knowledge, students learn many other skills that should be mentioned in the learning outcomes of the course. The students’ background, such as their prior knowledge, learning style and culture, affects how they learn in a course. A survey was conducted to map the learning styles of computer science students and to see if their cultural background affected their learning style. A statistical analysis of the data indicated that computer science students are different learners than engineering students in general and that there is a connection between the student’s culture and learning style. In this thesis, a simple self-assessment scale that is based on Bloom’s revised taxonomy has been developed. A statistical analysis of the test results indicates that in general the scale is quite reliable, but single students still slightly overestimate or under-estimate their knowledge levels. For students, being able to follow their own progress is motivating, and for a teacher, self-assessment results give information about how the class is proceeding and what the level of the students’ knowledge is.

Applying Qt to programming courses

Työn tavoitteena on sovittaa Qt opetussuunnitelmaan. Työ sisältää Qt:n lyhyen historian sekä katsauksen sen nykytilaan. Nykytilakatsaus sisältää kolme näkökulmaa: miten ja missä Qt:ta voidaan käyttää, sekä sen käyttötarkoitukset teollisuudessa ja opetuksessa. Työn tuloksena syntyy luentodemonstraatiota varten pieni ohjelma, joka on luotu C++:n ja Qt Designerin avulla ja käyttää olennaisia käyttöliittymäkirjaston olioita. Toisena tuotteena työssä syntyy luonnos Lappeenrannan Teknillisen Yliopiston ohjelmointikursseista, joissa Qt:ta voitaisiin käyttää avustamaan opiskelijoita näkemään, miten graafinen ohjelma luodaan sekä valmentaa heitä ymmärtämään viitekehyksien ja graafisten kirjastojen tuomat edut.

Some reformulations for the quadratic assignment problem

Kombinatorisk optimering handlar om att hitta en bra eller rent av den bästa möjliga lösningen från ett känt antal lösningar eller kombinationer. Ofta är antalet lösningar så enormt att en genomgång av alla olika lösningar inte är möjlig. En av huvudorsakerna till att det forskas inom kombinatorisk optimering är att liknande frågeställningar eller problem uppkommer inom så många olika områden. Påståendet stämmer speciellt bra för kvadratiska tilldelningsproblem(eng. Quadratic Assignment Problem). Sådana problem uppstår då man försöker beskriva en stor mängd tillämpade frågeställningar. Vilken gate skall väljas för flygen på större flygplatser för att minimera den totala väg människorna behöver gå och bagaget förflyttas? Var skall olika avdelningar på en fabrik placeras för att minimera materialförflyttningar mellan avdelningarna? Hur ser ett optimalt tangentbord ut för olika språk? Var skall komponenterna placeras på ett kretskort? De här är alla frågor som kan besvaras genom att lösa kvadratiska tilldelningsproblem. Kvadratiska tilldelningsproblem är dock mycket svåra att lösa. Det beror på att problemet i den standardform det matematiskt formuleras i huvudsak består av produkter av binära variabler. I denna avhandling har problemet omformulerats till en linjär diskret form som innehåller färre variabler. Med omformuleringen har bland annat flera tidigare olösta kvadratiska tilldelningsproblem kunnat lösas till globalt optimum, den bästa möjliga lösningen, för första gången någonsin.

Scheduling dynamic dataflow graphs with model checking

With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

Susteinable steelmaking by process integration

Environmental issues, including global warming, have been serious challenges realized worldwide, and they have become particularly important for the iron and steel manufacturers during the last decades. Many sites has been shut down in developed countries due to environmental regulation and pollution prevention while a large number of production plants have been established in developing countries which has changed the economy of this business. Sustainable development is a concept, which today affects economic growth, environmental protection, and social progress in setting up the basis for future ecosystem. A sustainable headway may attempt to preserve natural resources, recycle and reuse materials, prevent pollution, enhance yield and increase profitability. To achieve these objectives numerous alternatives should be examined in the sustainable process design. Conventional engineering work cannot address all of these substitutes effectively and efficiently to find an optimal route of processing. A systematic framework is needed as a tool to guide designers to make decisions based on overall concepts of the system, identifying the key bottlenecks and opportunities, which lead to an optimal design and operation of the systems. Since the 1980s, researchers have made big efforts to develop tools for what today is referred to as Process Integration. Advanced mathematics has been used in simulation models to evaluate various available alternatives considering physical, economic and environmental constraints. Improvements on feed material and operation, competitive energy market, environmental restrictions and the role of Nordic steelworks as energy supplier (electricity and district heat) make a great motivation behind integration among industries toward more sustainable operation, which could increase the overall energy efficiency and decrease environmental impacts. In this study, through different steps a model is developed for primary steelmaking, with the Finnish steel sector as a reference, to evaluate future operation concepts of a steelmaking site regarding sustainability. The research started by potential study on increasing energy efficiency and carbon dioxide reduction due to integration of steelworks with chemical plants for possible utilization of available off-gases in the system as chemical products. These off-gases from blast furnace, basic oxygen furnace and coke oven furnace are mainly contained of carbon monoxide, carbon dioxide, hydrogen, nitrogen and partially methane (in coke oven gas) and have proportionally low heating value but are currently used as fuel within these industries. Nonlinear optimization technique is used to assess integration with methanol plant under novel blast furnace technologies and (partially) substitution of coal with other reducing agents and fuels such as heavy oil, natural gas and biomass in the system. Technical aspect of integration and its effect on blast furnace operation regardless of capital expenditure of new operational units are studied to evaluate feasibility of the idea behind the research. Later on the concept of polygeneration system added and a superstructure generated with alternative routes for off-gases pretreatment and further utilization on a polygeneration system producing electricity, district heat and methanol. (Vacuum) pressure swing adsorption, membrane technology and chemical absorption for gas separation; partial oxidation, carbon dioxide and steam methane reforming for methane gasification; gas and liquid phase methanol synthesis are the main alternative process units considered in the superstructure. Due to high degree of integration in process synthesis, and optimization techniques, equation oriented modeling is chosen as an alternative and effective strategy to previous sequential modelling for process analysis to investigate suggested superstructure. A mixed integer nonlinear programming is developed to study behavior of the integrated system under different economic and environmental scenarios. Net present value and specific carbon dioxide emission is taken to compare economic and environmental aspects of integrated system respectively for different fuel systems, alternative blast furnace reductants, implementation of new blast furnace technologies, and carbon dioxide emission penalties. Sensitivity analysis, carbon distribution and the effect of external seasonal energy demand is investigated with different optimization techniques. This tool can provide useful information concerning techno-environmental and economic aspects for decision-making and estimate optimal operational condition of current and future primary steelmaking under alternative scenarios. The results of the work have demonstrated that it is possible in the future to develop steelmaking towards more sustainable operation.