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This research paper focuses on the implementation and evaluation of Minervini's momentum analysis techniques in an algorithmic approach. The study aimed to assess the limitations and challenges associated with executing Minervini's strategy in an algorithmic trading system. Several technical restrictions, practical application problems, and the exclusion of fundamental and catalyst aspects contribute to the implementation of a primitive variant of Minervini's strategy. The challenges included the subjective nature of base patterns making bases difficult to identify and limitations in risk and position sizing. However, despite the challenges, the algorithmic approach offers advantages such as the ability to analyze a large number of stocks rapidly. It is suggested to use the algorithm as a tool for stock exclusion rather than fully automating the buying and selling decisions. The research investigates the possibility of generating excess returns in Sweden, Denmark, and Finland using the implemented algorithm over different time periods from 2008 to 2023. Hundreds of stocks were divided up into 18 stock portfolios based on market capitalization size calculations for a given year. These portfolios were traded using both the momentum strategy and an index strategy. The empirical results indicate that small-cap portfolios exhibited consistent excess returns compared to mid-cap and large-cap portfolios, particularly during high volatility periods. However, the research did not account for transaction costs, which are essential to evaluate the strategy's net returns in real-world scenarios. Despite the exclusion of transaction costs in the study, the significant excess returns observed in small-cap portfolios indicate that the implemented momentum strategy performs notably better for small-cap stocks compared to mid-cap and large-cap stocks. This finding contradicts the efficient market hypothesis, assuming equal transaction costs across different market capitalizations. Further research should consider incorporating transaction costs to gain a more comprehensive understanding of the strategy's overall performance and its practical implications for various market segments. Future research should consider incorporating transaction costs and optimizing the stop-loss and profit-taking levels, and exploring a weekly-based approach instead of a daily-based approach. Additionally, volume analysis, data handling improvements, and a more detailed analysis of buy and sell decisions are recommended to optimize the algorithm's performance for future research. To summarize, while the implemented algorithm does not fully mimic Minervini's strategy, it offers valuable insights and potential value, especially in small-cap stocks. Further research and optimization are required to enhance its effectiveness and address the identified limitations.

Sequential decision problems under uncertainty are commonly studied with stochastic programing. An important modeling choice is the number of stages. More stages allow additional information to be captured, but is associated with a coarser representation of uncertainty may worsen solution quality. In this paper, we study this trade-off, with the objective to advance the understanding of how the number of stages affect solution quality in stochastic programing. We show: (i) how the optimistic bounds from stochastic programing gradually suggest improved performance with more stages, while the real solution quality simultaneously deteriorates; and (ii) that real performance can be improved by adding stages, but only up to some point, after which more stages are detrimental. Further, we highlight the importance of understanding what creates the value of more stages in the problem of interest, and particularly if this can be captured in models with few stages. The numerical experiments are based on the classic portfolio choice problem of an investor with constant relative risk aversion preferences, maximizing the expected utility of terminal wealth. We study instances with proportional transaction costs and predictability in returns, which takes this problem into an inherently multi-stage nature. Funding Agencies|Swedens Innovation Agency [2019-04798]; University of Chicago Booth School of BusinessUniversity of Chicago

In light of a circular economy, to encourage core returns, the remanufacturer charges a deposit and refund it to the customer based on quality inspection of cores. Generally, two types of classification errors exist and interact with each other during the inspection process: either low-quality cores are sorted as remanufacturable, or high-quality cores are sorted as non-remanufacturable. The remanufacturer needs to choose refund policies and determine a reasonable deposit value, considering customers potential responses. This paper firstly develops analytical solutions for these issues within a game theory framework. The effect of inspection information transparency is evaluated by comparing two settings: the information of inspection errors is available to customers or not. The study results show the advantage of inspection information transparency from the remanufacturers perspective. The analysis indicates the importance of avoiding overestimating customers payoff of products and the significance of inspection accuracy. The study also highlights that the salvage value of different cores significantly influences the remanufacturers profits, and the improvement of inspection accuracy does not necessarily reduce the customers return of low-quality cores.

MRP theory concerns production-inventory systems, in which produced items are made up of sets of sub-items, either produced or purchased (imported into the system) and required to be available a lead-time before the product is completed. The hierarchical dependence of relations between items is captured by the use of input matrices from Input-Output Analysis, the necessary advanced timing by applying the methodology of Laplace transforms, and the production-economic consequences by the net present value (NPV). This theory has been developed for about 40 years, but little attention has been given to transient aspects, i.e. when there happens to be an initial available inventory of items usable in future production. In this paper, we attempt to highlight the theoretical consequences from having a positive initial available inventory.

Determining the economic lot size has always represented one of the most important issues in production planning. This problem has long attracted the attention of researchers, and several models have been developed to meet requirements at minimum cost. In this paper we explore and discuss the evolution of these models during one hundred years of history, starting from the basic model developed by Harris in 1913, up to today. Following Harris׳s work, a number of researchers have devised extensions that incorporate additional considerations. The evolution of EOQ theory strongly reflects the development of industrial systems over the past century. Here we outline all the research areas faced in the past by conducting a holistic analysis of 219 selected journal papers and trying to give a comprehensive view of past work on the EOQ problem. Finally, a new research agenda is proposed and discussed.

Process industries has for long been important for the development of Swedish industry and society. All industries face different conditions that affect how to best run their operations. This thesis aims to describe some of the conditions that characterize process industries compared to other industries. Further one of these characteristics has been studied more closely. One of the traits of process industries is that they are positioned at the start of the transformation process close to the raw material mixing, separating or forming it into products often used for further transformation. Process industries hence become dependent on the properties of these materials. One of the most prominent characteristics inherent from the raw material properties is the divergent bill of material. The divergent bill of material originates from the fact that a given raw material is made up of different components that will yield several products with different characteristics when processed. When splitting the raw material into the desired products the yielded products from a certain raw material usually have different value to the producer, some more desired than others. These multiple products generated poses a challenge from a planning perspective raising questions like “How should we balance the supply and demand of all the products produced?”, “What shall we do with the excess products produced?”. The first paper in this thesis describe the production planning in four Swedish process industries with the ultimate aim to connect their planning to the supply chain characteristics they face as process industries. The study concludes that the industry specific conditions mainly affect planning at short time ranges when planning becomes more detailed. In general the use of planning or decision support systems is low, stemming from a, warranted or not, belief that general decision support systems do not fit process industries. Another finding is that the case companies mainly operate in niche markets. This study also highlighted that the planning complexity arising from characteristic of co- and by-product generation in combination with the lack of decision support systems requires further studies. The subsequent two papers focus on supply chain planning and coordination with a divergent bill of material. They present a mathematical model over the supply chain planning in a real case company in the specialty oils industry. The second paper investigates transfer pricing as a coordination tool by comparing decentralised supply chain planning with centralized planning in an integrated model. Transfer pricing is found to have a potential positive effect on supply chain planning while simultaneously creating problems in terms of uneven distribution of the contribution margin among supply chain partners. Finally the third paper more closely investigates different ways to set transfer prices and comparing them to the optimal transfer prices. Setting optimal transfer prices with a divergent bill of material has proven to be less straightforward than the case with no dependencies between products. Some optimal transfer prices could even be set lower than the marginal cost for producing them due to the dependency between the products in the divergent bill of material. This indicates that there is an opportunity cost for a product that is dependent on the demand of other products. Processindustrier har länge varit viktiga för utvecklingen av svensk industri och det svenska samhället. Alla branscher möter olika förutsättningar som påverkar hur verksamheten bäst skall drivas. Avhandlingen syftar till att beskriva några av de villkor som kännetecknar processindustrin jämfört med andra branscher. Slutligen har en av dessa kännetecknande egenskaper studerats närmare. En av de egenskaper som utmärker processindustrier är att de är positionerade vid början av omvandlingsprocessen nära råvaran och blandar, separerar eller formar den till produkter som ofta används för ytterligare förädling. Processindustrin blir därmed beroende av egenskaperna hos råmaterialet som används. En av de mest framträdande egenskaperna härrörande från dessa råmaterialegenskaper är det divergenta materialflödet. Det divergerande materialflödet har sitt ursprung i att ett visst råmaterial består av olika komponenter som ger flera produkter med olika egenskaper. När råmaterialet separeras i sina komponenter erhålls flera produkter som kan ha väldigt olika värde för producenten. Efterfrågan på de produkter som erhålls ur separeringen kan vara vitt skild från vad som erhålls ur produktionsprocessen. Denna obalans mellan efterfrågan och försörjning är en utmaning ur ett planeringsperspektiv och väcker frågor som " Hur ska efterfrågan och försörjning av de produkter som produceras balanseras?", "Hur skall överskottet på vissa produkter hanteras? ". Den första artikeln i denna avhandling beskriver produktionsplaneringen i fyra svenska processindustriföretag inom områdena pappersmassa, specialkemi, specialoljor samt papper och pappersmassa. Målet med studien var att jämföra planeringen av försörjningskedjan med de förutsättningar som processindustrin ställs inför. I studien dras slutsatsen att de branschspecifika förhållandena främst påverkar den kortsiktiga planeringen med mer detaljer. I allmänhet verkar användningen av planerings- eller beslutsstödsystem vara låg, som härrör från en, befogat eller inte, tro att generella beslutsstödssystem inte passar processindustri. Fallföretagen förefaller också huvudsakligen vara verksamma på nischmarknader. Denna studie betonar också vikten av djupare studier av energiplanering samt den planeringskomplexitet som uppkommer till följd av divergerande materialflöden. De två efterföljande artiklarna fokuserar på planering och koordinering av försörjningskedjan vid ett divergerande materialflöde. De presenterar en matematisk modell över försörjningskedjan i ett fallföretag som tillverkar specialoljor. Den andra artikeln undersöker effekter av att använda internprissättning som verktyg för koordinering av försörjningskedjor genom att jämföra decentraliserad försörjningskedjeplanering med en fullt integrerad centraliserad planering. Internprissättning visar sig ha potentiellt positiva effekter på planeringen av försörjningskedjan men skapar samtidigt problem i form av att täckningsbidraget kan fördelas väldigt ojämnt mellan partner i försörjningskedjan. Slutligen behandlar den tredje artikeln olika sätt att bestämma internpriser och utvärderar deras koordineringseffekter på försörjningskedjan genom att jämföra med optimal satta internpriser. Att bestämma optimala internpriser med ett divergerande materialflöde har visat sig bli komplicerat i och med det beroende som finns mellan produkterna som kommer från samma råmaterial. Optimala internpriser har visat sig kunna vara både avsevärt högre och avsevärt lägre än marginalkostanden för att producera dem. Detta indikerar att alternativkostnaden för en produkt kan påverkas starkt av efterfrågan på andra produkter den har en koppling till via råmaterialet de båda produceras från.

The overall purpose of the PhD project is to develop a framework for making optimal decisions on the equity derivatives markets. Making optimal decisions refers e.g. to how to optimally hedge an options portfolio or how to make optimal investments on the equity derivatives markets. The framework for making optimal decisions will be based on stochastic programming (SP) models, which means that it is necessary to generate high-quality scenarios of market prices at some future date as input to the models. This leads to a situation where the traditional methods, described in the literature, for modeling market prices do not provide scenarios of sufficiently high quality as input to the SP model. Thus, the main focus of this thesis is to develop methods that improve the estimation of option implied surfaces from a cross-section of observed option prices compared to the traditional methods described in the literature. The estimation is complicated by the fact that observed option prices contain a lot of noise and possibly also arbitrage. This means that in order to be able to estimate option implied surfaces which are free of arbitrage and of high quality, the noise in the input data has to be adequately handled by the estimation method. The first two papers of this thesis develop a non-parametric optimization based framework for the estimation of high-quality arbitrage-free option implied surfaces. The first paper covers the estimation of the risk-neutral density (RND) surface and the second paper the local volatility surface. Both methods provide smooth and realistic surfaces for market data. Estimation of the RND is a convex optimization problem, but the result is sensitive to the parameter choice. When the local volatility is estimated the parameter choice is much easier but the optimization problem is non-convex, even though the algorithm does not seem to get stuck in local optima. The SP models used to make optimal decisions on the equity derivatives markets also need generated scenarios for the underlying stock prices or index levels as input. The third paper of this thesis deals with the estimation and evaluation of existing equity market models. The third paper gives preliminary results which show that, out of the compared models, a GARCH(1,1) model with Poisson jumps provides a better fit compared to more complex models with stochastic volatility for the Swedish OMXS30 index. Det övergripande syftet med doktorandprojektet är att utveckla ett ramverk för att fatta optimala beslut på aktiederivatmarknaderna. Att fatta optimala beslut syftar till exempel på hur man optimalt ska hedga en optionsportfölj, eller hur man ska göra optimala investeringar på aktiederivatmarknaderna. Ramverket för att fatta optimala beslut kommer att baseras på stokastisk programmerings-modeller (SP-modeller), vilket betyder att det är nödvändigt att generera högkvalitativa scenarier för marknadspriser för en framtida tidpunkt som indata till SP-modellen. Detta leder till en situation där de traditionella metoderna, som finns beskrivna i litteraturen, för att modellera marknadspriser inte ger scenarier av tillräckligt hög kvalitet för att fungera som indata till SP-modellen. Följaktligen är huvudfokus för denna avhandling att utveckla metoder som, jämfört med de traditionella metoderna som finns beskrivna i litteraturen, förbättrar estimeringen av ytor som impliceras av en given mängd observerade optionspriser. Estimeringen kompliceras av att observerade optionspriser innehåller mycket brus och möjligen också arbitrage. Det betyder att för att kunna estimera optionsimplicerade ytor som är arbitragefria och av hög kvalitet, så behöver estimeringsmetoden hantera bruset i indata på ett adekvat sätt. De första två artiklarna i avhandlingen utvecklar ett icke-parametriskt optimeringsbaserat ramverk för estimering av högkvalitativa och arbitragefria options-implicerade ytor. Den första artikeln behandlar estimeringen av den risk-neutrala täthetsytan (RND-ytan) och den andra artikeln estimeringen av den lokala volatilitetsytan. Båda metoderna ger upphov till jämna och realistiska ytor för marknadsdata. Estimeringen av RND-ytan är ett konvext optimeringsproblem men resultatet är känsligt för valet av parametrar. När den lokala volatilitetsytan estimeras är parametervalet mycket enklare men optimeringsproblemet är icke-konvext, även om algoritmen inte verkar fastna i lokala optima. SP-modellerna som används för att fatta optimala beslut på aktiederivatmarknaderna behöver också indata i form av genererade scenarier för de underliggande aktiepriserna eller indexnivåerna. Den tredje artikeln i avhandlingen behandlar estimering och evaluering av existerande modeller för aktiemarknaden. Den tredje artikeln tillhandahåller preliminära resultat som visar att, av de jämförda modellerna, ger en GARCH(1,1)-modell med Poissonhopp en bättre beskrivning av dynamiken för det svenska aktieindexet OMXS30 jämfört med mer komplicerade modeller som innehåller stokastisk volatilitet.

Supply chains have expanded rapidly over the decades, with the aim to increase productivity, lower costs and fulfil demands in emerging markets. The increasing complexity in a supply chain hinders visibility and consequently reduces one’s control over the process. Cases of disruption such as the ones faced by Ericsson and Enron, have shown that a risk event occurring at one point of the supply chain can greatly affect other members, when the disruption is not properly controlled. Supply chain management thus faces a pressing need to maintain the expected yields of the system in risk situations. To achieve that, we need to both identify potential risks and evaluate their impacts, and at the same time design risk mitigation policies to locate and relocate resources to deal with risk events. This dissertation aims to analyse how supply chain risks could be effectively managed. This is done firstly by positioning the research agenda in supply chain risk management (SCRM). Then, methods for effective management of supply chain risk are identified and analysed. In order to find these, we develop a research framework in which the supply chain system is divided into subsystems based on the operations of make, source and deliver; as well as on material, financial and information flows. Furthermore, research questions are raised in order to understand the impact of risks on supply chains, to identify the performance measures for monitoring supply chains, and to determine risk mitigation strategies for improving system performances. This dissertation includes a bibliometric analysis of relevant literature of SCRM published in recent years. Based on the co-citation analysis, we identify the changing interest in SCRM, from performance-focused individual issues in the early years to integrated system issues with management perspective in recent years. We also identify the growing importance of information issues in SCRM. However, there is a relative lack of research into risk mitigation focusing on information flows in the literature. This dissertation also develops a conceptual model for analysing supply chain risk. The adoption of tools from the established field of reliability engineering provides a systematic yet robust process for risk analysis in supply chains. We have found that the potential use of a stand-alone tool of Failure Modes and Effect Analysis (FMEA) or a hybrid application of Fault Tree Analysis (FTA) and Analytical Hierarchy Process (AHP), will be most appropriate in SCRM. Apart from above mentioned studies, this dissertation then includes three manuscripts respectively investigating the risk mitigation policies in SCRM. First, we suggest a dynamic pricing policy when facing supply yield risk, such as price postponement, where price is determined only after receiving the delivery information. This postponed pricing, can improve the balance between supply and demand, especially when the delivery quantity is small, demand has a low uncertainty and there is a wide range when demand is sensible to price change. In another paper, a system dynamics model is developed to investigate the dispersion of disruption on the supply chain operation as well as along the network. Based on this simulation model, policies are tested to observe their influence to the performance of the supply chain. The study results support the benefit of a dual-sourcing strategy. Furthermore, information sharing, appropriate order splitting and time to react would further improve the supply chain performance when disruption strikes. In the last paper, we study how capacity should be expanded when a new product is introduced into the market. The major risk here is due to a quick capacity expansion with large investments which could be difficult to recover. Using the Bass diffusion model to describe demand development, we study how capacity expansion, together with sales plan could affect the economics of the system. Using sales information for the forecast, delaying the sales and adding initial inventories, should create a better scheme of cash flows. This dissertation contributes in several ways to the research field of SCRM. It plots research advancements which provide further directions of research in SCRM. In conjunction with the conceptual model, simulations and mathematical modelling, we have also provided suggestions for how a better and more robust supply chain could be designed and managed. The diversified modelling approaches and risk issues should also enrich the literature and stimulate future study in SCRM.

Exergy is a concept that is gaining an increasingly wider recognition as a proper measure for the actual energy resources consumed, when energy is used. Energy as such is indestructible, but exergy is not. As entropy is generated while energy is used, exergy is consumed. Exergy can be interpreted as the qualitative content of energy, or as energy in its highest quality. Therefore, there is an interest in investigating this concept from as many theoretical aspects as possible. In earlier papers the author has developed formulae for the exergy potential of a system of finitely extended objects, not necessarily having any environment. It was shown that the classical formula for exergy obtains as one of the objects grows beyond all bounds thereby taking on the rôle as an environment. In this current paper formulae are derived for the exergy content of an isolated body in thermodynamic disequilibrium, viewed as a system of infinitely many objects each with infinitesimal extension and in microscopic equilibrium.

This thesis addresses industrial energy issues from a production economic perspective. During the past decade, the energy issue has become more important, partly due to rising energy prices in general, but also from a political pressure on environmental awareness concerning the problems with climate change. As a large user of energy the industry sector is most likely responsible for a lot of these problems. Things need to change and are most likely to do so considering current and assumed future governmental regulations. Thus, the energy intensive process industries studied and focused on in this thesis exemplify the importance of introducing a strategic perspective on energy, an appropriate approach for planning, as well as the possibilities of including energy issues in a production and supply chain planning model. The thesis aims to provide models, methods and decision support tools for energy related production and supply chain planning issues of relevance for process industries as well as for other energy intensive industries. The overall objectives are to analyze the strategic importance of energy management, production and supply chain planning, and the opportunities provided when energy is included in a production and supply chain planning model. Three different studies are carried out, analyzed, and presented as in this thesis. The first study is a case study at a specialty chemicals company and resulted in the first paper. Since the energy issue is not only a cost issue driven by supply and demand, but also a political issue due to its environmental aspects, it is likely to believe that political influence and especially continuity will have escalating effect on the energy intensive process industry sector. Thus, the strategic dimension of energy is highly relevant in this thesis. The importance of organizational integration, having a main responsible person, locating core business, and political continuity are addressed as prerequisites for including energy into the corporate strategy. Regarding long term profitability, the importance of correctly utilizing the energy system by appropriate energy planning and with respect to energy efficiency and effectiveness in both flexibility and investment issues are addressed. Further on, the quest of finding alternative revenue while striving for a proper exergy usage is addressed. The second study is a multiple case study with four different case companies involved; pulp, specialty chemicals, specialty oils, as well as a pulp and paper company. The need for improved production and supply chain planning is also addressed where for instance the lack of planning support for process industries is still an area of improvement. The production and supply chain planning in process industries is found to be rather poor compared to regular manufacturing companies. The planning methods found are often tailor made and adapted to the individual characteristics that are typical for many process industries. It has further on been difficult to distinguish similarities and differences among process industries regarding these planning issues and thus hard to generalize. The third study focuses on mathematical modelling and programming developing a combined supply chain and energy optimization model for a pulp company. Taking the first papers together there are reasons to believe that a planning and optimization model that take energy aspects in consideration, as a previously missing link, will contribute to improve the operations in process industries. A clear impact of involving energy issues into the supply chain planning is shown. The results show that a different production schedule is optimal when the energy issues are applied, and depend on, for instance, variations in energy prices such as the one for electricity. This is shown by using a model for a supply chain where the energy flow, and especially the utilization of by-products, also is involved.

Purpose – The purpose of this master thesis is to explore how an e-tailer selling bulky items can use a multiple criteria ABC analysis to make its purchasing process more effective, while balancing richness and reach, with the performance measurements of profitability, total asset turnover and inventory turnover. The purpose will be accomplished through a single case study on an e-tailer active on the Swedish furniture and home furnishing market. Methodology – This thesis applies a multiple criteria ABC-analysis to a single case study. The approach is semi-deductive as theory is combined with interviews on how to match and adapt theory about inventory control and purchasing with the specific requirements of an e-tailer selling bulky items. Findings – This thesis has resulted in a set of recommendations that aim to make the purchasing process of an e-tailer more effective. That is, capital and inventory space will be better allocated to the e-tailer’s more profitable items. Among other things, this thesis shows how dead articles can be identified and how a purchaser can prioritize more profitable articles over less profitable ones when making procurement decisions. The other recommendations are for the e-tailer to investigate the possibilities of decoupling the supply chain by keeping stock at the suppliers’ premises, to match the supplier reliability with their importance in the supply chain, and lastly to explore possibilities of drop shipment. Further, the main finding is that a comparison between the A-, B-, and C-classes and the reliability of the suppliers, highlights a gap and a possible risk. Put differently, the importance of a specific item for the business should be reflected in the choice of supplier and the multiple criteria ABC analysis is the tool to illustrate the importance. Keywords – E-commerce, E-tailer, richness, reach, transaction cost, ABC analysis, multiple criteria ABC, MCABC, inventory turnover ratio, supplier selection, purchasing Paper type – Masters thesis Syfte – Syftet med detta examensarbete är att undersöka hur en e-handelsdetaljist som säljer skrymmande artiklar kan använda en flerdimensionell ABC-analys för att göra sin inköpsprocess mer effektiv och balansera richness och reach, med mätetal som lönsamhet, kapitalomsättningshastighet och lageromsättningshastighet. Syftet kommer att uppfyllas genom en fallstudie på en e-handelsdetaljist verksam på den svenska möbel- och heminredningsmarknaden. Metod – Denna fallstudie använder sig av en flerdimensionell ABC-analys. Tillvägagångssättet är semi-deduktivt då intervjuer och teori om hur lagerstyrning och inköp kan matchas och anpassas till ett företags specifika behov. Resultat – Den här uppsatsen har resulterat i en rad åtgärder som syftar till att göra en ehandlares inköpsprocess mer effektiv. På så vis att kapital och lageryta bättre allokeras till ehandlarens lönsamma artiklar. Bland annat visar den här uppsatsen hur döda artiklar kan identifieras och hur inköparen kan prioritera mer lönsamma artiklar över olönsamma vid inköp. De andra åtgärdena handlar om att undersöka möjligheter att frikoppla försörjningskedjan genom att lagra produkter hos leverantören, att matcha leverantörernas pålitlighet och deras betydelse i försörjningskedjan, och slutligen att utforska möjligheter att utöka drop shipment. Det främsta bidraget är att eventuella felprioriteringar och risker blir tydliga genom en jämförelse mellan A-, B- och C-klasserna och leverantörernas pålitlighet. Med andra ord bör den affärsmässiga inverkan som respektive artikel har på e-handlarens resultat avspegla sig i valet av leverantör. En flerdimensionell ABC-analys kan användas för att påvisa respektive artikels affärsmässiga inverkan. Publikationstyp – Examensarbete för utbildning till civilingenjör (masteruppsats).

Management of production activities covers a wide range of decisions. In this paper, a modularised approach is suggested that, through configuration, generates a case-specific flow design. The approach is based on identification of decision categories that are generic and fundamental in the flow design, covering both discrete manufacturing industries and process industries. Each decision category identifies a unique property of the flow which changes at a particular point: this is termed a decoupling point. A three-dimensional modularised typology is developed by combining three different decision categories. Cases from the steel industry and the tooling industry are used to illustrate how the typology can be applied. The modularised approach provides a typology for the application of both qualitative and quantitative methods for flow management, including planning, control and performance management. Funding Agencies|Swedish Foundation for Strategic Research [PIC-LI]; Process Industrial IT and Automation (PiiA) - VINNOVA; Swedish Energy Agency, Formas; Swedish industry [2014-05110]

This paper suggests a modularized sales and operations planning (S&OP) framework, consisting of content and process. The framework’s content is based on a typology of decoupling points in which the effect of decoupling points on the decision variables in S&OP is studied. The framework’s process takes a step back and addresses the need for a more elaborate design to precede the operational use of S&OP content for different production contexts. The framework supports both process industries (PIs) and discrete manufacturing industries (DIs), and recognizes their specific requirements and reflects them in their S&OP. The differentiating characteristics of PIs and DIs are emphasized through three different decoupling points, namely: discretization decoupling point, control mode decoupling point, and customer order decoupling point. The suggested framework aims to fill the gap in the literature regarding the lack of aggregate planning processes that match the PIs’ specific requirements by reflecting the differentiating characteristics of PIs in S&OP.

This dissertation is centered around two comprehensive themes: the extraction of information embedded in equity index option prices, and how to use this information in order to be able to make optimal decisions in the equity index option markets. These problems are important for decision makers in the equity index options markets, since they are continuously faced with making decisions under uncertainty given observed market prices. The methods developed in this dissertation provide robust tools that can be used by practitioners in order to improve the quality of the decisions that they make. In order to be able to extract information embedded in option prices, the dissertation develops two different methods for estimation of stable option implied surfaces which are consistent with observed market prices. This is a difficult and ill-posed inverse problem which is complicated by the fact that observed option prices contain a large amount of noise stemming from market micro structure effects. Producing estimated surfaces that are stable over time is important since otherwise risk measurement of derivatives portfolios, pricing of exotic options and calculation of hedge parameters will be prone to include significant errors. The first method that we develop leads to an optimization problem which is formulated as a convex quadratic program with linear constraints which can be solved very efficiently. The second estimation method that we develop in the dissertation makes it possible to produce local volatility surfaces of high quality, which are consistent with market prices and stable over time. The high quality of the surfaces estimated with the second method is the crucial input to the research which has resulted in the last three papers of the dissertation. The stability of the estimated local volatility surfaces makes it possible to build a realistic dynamic model for the equity index derivatives market. This model forms the basis for the stochastic programming (SP) model for option hedging that we develop in the dissertation. We show that the SP model, which uses generated scenarios for the squared local volatility surface as input, outperforms the traditional hedging methods that are described in the literature. Apart from having an accurate view of the variance of relevant risk factors, it is when building a dynamic model also important to have a good estimate of the expected values, and thereby risk premia, of those factors. We use a result from recently published research which lets us recover the real-world density from only a cross-section of observed option prices via a local volatility model. The recovered real-world densities are then used in order to identify and estimate liquidity premia that are embedded in option prices. We also use the recovered real-world densities in order to test how well the option market predicts the realized statistical characteristics of the underlying index. We compare the results with the performance of commonly used models for the underlying index. The results show that option prices contain a premium in the tails of the distribution. By removing the estimated premia from the tails, the resulting density predicts future realizations of the underlying index very well.

Managers and researchers are increasingly interested in the factor that logistics enterprise competitiveness(LEC) has significant effects on the development of Chinese logistics enterprises, especially in view of theenterprise life cycle. This paper investigates the contents and evolution of the composing factors of LEC inChina by a survey.With Statistical Product and Service Solutions (SPSS 15.0) software, the factor analysismethod is used to determine the effects of each factor on LEC. Furthermore, the comparative analysismethod is applied to compare the composing factors of LEC in different types of logistics enterprises andat different enterprise life cycle stages. The results show that factors of LEC according to their descendingimportance level are corporate capabilities, corporate resources, and dynamic mechanism. Three kindsof corporate capabilities (financial management capability, logistics risk control capability, and humanresource management capability) and two kinds of corporate resources (corporate human resources andcorporate culture) have the greatest influence on the development of LEC, but in reality have poor practicalperformance, and hence deserve more consideration from the enterprises. National Natural Science Foundation of China Humanity and Social ScienceYouth Foundation of Ministry of Education of China China State Scholarship Fund China State Scholarship Fund

The dynamic lotsizing problem concerns the determination of optimally produced/delivered batch quantities, when demand, which is to be satisfied, is distributed over time in different amounts at different times. The standard formulation assumes that these batches are provided instantaneously, i.e. that the production rate is infinite. Using a cumulative geometrical representation for demand and production, it has previously been demonstrated that the inner-corner condition for an optimal production plan reduces the number of possible optimal replenishment times to a finite set of given points, at which replenishments can be made. The problem is thereby turned into choosing from a set of zero/one decisions, whether or not to replenish each time there is a demand. If n is the number of demand events, this provides 2n−1 alternatives, of which at least one solution must be optimal. This condition applies, whether an Average Cost approach or the Net Present Value principle is applied, and the condition is valid in continuous time, and therefore in discrete time. In the current paper, the assumption of an infinite production rate is relaxed, and consequences for the inner-corner condition are investigated. It is then shown that the inner-corner condition needs to be modified to a tangency condition between cumulative requirements and cumulative production. Also, we have confirmed the additional restriction for feasibility in the finite production case (provided by Hill, 1997), namely the production rate restriction. Furthermore, in the NPV case, one further necessary condition for optimality, the distance restriction concerning the proximity between adjacent production intervals, has been derived. In an example this condition has shown to reduce the number of candidate solutions for optimality still further. An algorithm leading to the optimal solution is presented.

To make a difference among the energy intensive process industries, this dissertation addresses production planning and supply chain planning problems related to industrial energy management issues. The energy issue is turning more and more important from different angles, involving price as well as environmental problems due to climate change leading to political pressure on all energy users. The process industry sector is one of the largest users of energy, and thus important to analyse. Process industries are also capital intensive and operate on large and expensive process equipment, making it imperative to plan their production well in order to reach preferable capacity utilisation. Therefore this dissertation strives to locate the most important energy management issues for the long term profitability of process industries, and investigates the symbiotic effects of including energy issues in production and supply chain planning. Three different studies at three case companies are carried out, analysed, and presented in five papers. The cases represent the process industry sectors: chemicals, pulp, and steel. Both qualitative case study methodologies as well as quantitative mathematical modelling and optimisation approaches have been practiced. The research questions are analysed from both an energy system and from a production process point of view, separately as well as combined. Energy is somewhat considered to be the main workforce for process industries and this dissertation exemplifies some of its most important dimensions in this context. Several prerequisites for putting energy management on the strategic agenda are located in a specialty chemical industry where the importance of introducing a strategic perspective on energy, the way energy is used, and the possibilities of increasing alternative revenue from utilising by- and/or co-products differently are pinpointed. Approaches for including energy issues in planning processes are also suggested in terms of a MILP model for the entire supply chain of a pulp company, including decisions on purchase and transportation of raw maerials, production allocation, energy mix, and distribution. Another example is presented based on the perspectives of economics of scale and lot sizing through economic order quantity principles in a steel company. By using real company data, energy smart approaches in planning and scheduling are developed with respect to the most important intersections between the production processes and their supporting energy system. The accumulated resource intensity and embedded energy could, and probably should, hence be more fairly reflected in the product price. The research finally shows some possible impact with including energy issues in a production and supply chain planning model. By planning differently, production prioritisations can be done, and it is not only possible without any large investments, but also prosperous with savings on both energy and money within reach. To conclude, planning of production and supply chain has either a direct or an indirect impact on the energy cost-effectiveness of a company. This dissertation argues that such impact also exists in its mutual form, and is very important when the energy issues are large enough, as they often are in the energy intensive process industry sector. Decision makers should thus beware of the short end of the stick that might be devastating in the long run, but also aware of all the possibilities that can bring success and prosperity when the future begins.

The dynamic lotsizing problem concerns the determination of optimal batch quantities, when given required amounts appear at discrete points in time. The standard formulation assumes that no shortages are allowed and that replenishments are made instantaneously. For the case when no shortage is allowed, previously it has been demonstrated that the inner-corner condition for an optimal production plan in continuous time reduces the number of possible replenishment times to a finite set of given points at which either a replenishment is made, or not. The problem is thus turned into choosing from a set of zero/one decisions with 2 n −1 alternatives, of which at least one solution must be optimal, where n is the number of requirement events. Recently, the instantaneous replenishment assumption has been replaced by allowing for a finite production rate, which turned the inner-corner condition into a condition of tangency between the cumulative demand staircase and cumulative production. In this paper we investigate relationships between optimal cumulative production and cumulative demand, when backlogging is permitted. The production rate is assumed constant and cumulative production will then be a set of consecutive ramps. Cumulative demand is a given staircase function. The net present value (NPV) principle is applied, assuming a fixed setup cost for each ramp, a unit production cost for each item produced and a unit revenue for each item sold at the time it is delivered. Among other results, it is shown that optimal cumulative production necessarily intersects the demand staircase. Instead of having 2 n −1 production staircases as candidates for optimality, there are 2 n −1 production structures as candidates. These are made up of sequences of batches, of which the set of batches may be optimised individually. Also is shown that the NPV of each batch has a unique timing maximum and behaves initially in a concave way and ends as convex. Results for the average cost approach are obtained from a zeroth/first order approximation of the objective function (NPV).

MRP theory provides a theoretical background for multi-level, multi-stage production-inventory systems (material requirements planning in a general sense) together with their economic evaluation, in particular applying the net present value principle. The theory combines the use of input-output analysis and Laplace transforms, the former for capturing product structures, and the latter for incorporating timing, including time lags, lead times, and output delays. In this paper, we consider any production policy, when given any external demand as a vector-valued function of time. It is shown that in order for available inventory to be kept at finite levels at any time, the lot-for-lot (L4L) solution must be valid for the time averages of production and deliveries, irrespective of the policy followed. This analysis is carried out using properties the Laurent expansions of the transforms involved.

The purpose of this paper is to investigate the research development in supply chain risk management (SCRM), which has shown an increasing global attention in recent years. Literature survey and citation/co-citation analysis are used to fulfil the research task. Literature survey has undertaken a thorough search of articles on selected journals relevant to supply chain operations management. Meanwhile, citation/co-citation analysis uses Web of Sciences database to disclose SCRM development between 1995 and 2009. Both the approaches show similar trends of rising publications over the past 15 years. This review has piloted us to identify and classify the potential risk associated with different flows, namely material, cash and information flows. Consequently, we identify some research gaps. Even though there is a pressing need and awareness of SCRM from industrial aspect, quantitative models in the field are relatively lacking and information flow risk has received less attention. It is also interesting to observe the evolutions and advancements of SCRM discipline. One finding is that the intellectual structure of the field made statistically significant increase during 2000-2005 and evolved from passively reacting to vague general issues of disruptions towards more proactively managing supply chain risk from system perspectives.

The integrated planning of transportation of raw material, production and distribution of products of the supply chain for a large pulp company is studied. The planning period is one year and a number of time periods are considered. The tactical decisions included in the model regard transportation of raw materials from harvest areas to pulp mills, production mix and contents at pulp mills, distribution of pulp products from mills to customers either via terminals or directly, and the selection of potential orders and their levels at customers. A mixed integer linear programming model for the supply chain problem is developed. The main solution method in this paper is a Lagrangian heuristic method based on Lagrangian decomposition. The heuristic divides the problem into two subproblems representing different physical stages in the supply chain, each including several time periods. The advantage of the proposed solution approach is that it generates feasible solutions of high quality in short time. A number of cases based on real data is analysed. Original Publication:Helene Lidestam and Mikael Ronnqvist, Use of Lagrangian decomposition in supply chain planning, 2011, Mathematical and computer modelling, (54), 9-10, 2428-2442.http://dx.doi.org/10.1016/j.mcm.2011.05.054Copyright: Elsevierhttp://www.elsevier.com/