Production and Logistics Systems Improvements - Biim Ultrasound AS

A crucial aspect of the supply chain network design process is deciding on optimal locations to situate new facilities. Facility location decisions rely on many factors, some of which might be conflicting with each other. The decision factors can be either quantitative or qualitative, thus a brute-force prioritization of one over another could be detrimental overall. To ensure the efficacy of the selection process, decision makers must consider both the quantitative and qualitative factors in tandem. Some of the common methods employed in the literature by organizations to facilitate their decision-making process include: optimization models and algorithms, decision support systems and computerized analytics tools. To this end, this thesis proposes a hybrid Multi-Criteria Decision Making (MCDM) model to aid the selection of an optimal location that suits the strategic fit of an organization. The proposed model integrates the Analytic Hierarchy Process (AHP) methodology for Multi-Attribute Decision Making (MADM) with Mixed Integer Programming (MIP). The solution is modeled and implemented with the AIMMS modeling language as well as the Gurobi Optimization tool in Python. This thesis work is based on a case study from Biim Ultrasound

Integrated Decision Making in Global Supply Chains and Networks

One of the more visible and often controversial effects of globalization is the rising trend in global sourcing, commonly referred to as outsourcing, offshoring or offshore outsourcing. Today, many organizations experience the necessity of growing globally in order to remain profitable and competitive. This research focuses on the process that organizations undergo in making strategic decisions of whether or not to go offshore, and then on the location and volume of these offshore operations.This research considers the strategic decision of offshoring and sub-divides it into two components: analysis of monetary benefits and evaluation of intangible variables. In this research, these two components are integrated by developing an analytical decision approach that can incorporate quantitative and qualitative factors in a structure based on multiple solution methodologies. The decision approach developed consists of two phases which concurrently assess the offshoring decision by utilizing mixed integer programming and multi-attribute decision modeling, specifically using Analytic Network Process, followed by multi-objective optimization and tradeoff analysis. The decision approach is further enhanced by employing engineering economic tools such as life cycle costing and activity based costing. As a result, the approach determines optimal offshoring strategies and provides a framework to investigate the optimality of the decisions with changing parameters and priorities.The applicability, compliance and effectiveness of the developed integrated decision making approach is demonstrated on two real life cases in two different industry types. Through empirical studies, different dimensions of offshoring decisions are examined, classified and characterized within the framework of the developed decision approach. The solutions are evaluated by their value, level of support and relevance to the decision makers.The utilization of the developed systematic approach showed that counterintuitive decisions may sometimes be the best strategy.This study contributes to the literature with a comprehensive decision approach for determining the most advantageous offshoring location and distribution strategies by integrating multiple solution methodologies. This approach can be adapted in the corporate world as a tool to improve global vision

Mixing Dyadic and Deliberative Opinion Dynamics in an Agent-Based Model of Group Decision-Making

International audienceIn this article, we propose an agent-based model of opinion diffusion and voting where influence among individuals and deliberation in a group are mixed. The model is inspired from social modeling, as it describes an iterative process of collective decision-making that repeats a series of interindividual influences and collective deliberation steps, and studies the evolution of opinions and decisions in a group. It also aims at founding a comprehensive model to describe collective decision-making as a combination of two different paradigms: argumentation theory and ABM-influence models, which are not obvious to combine as a formal link between them is required. In our model, we find that deliberation, through the exchange of arguments, reduces the variance of opinions and the proportion of extremists in a population as long as not too much deliberation takes place in the decision processes. Additionally, if we define the correct collective decisions in the system in terms of the arguments that should be accepted, allowing for more deliberation favors convergence towards the correct decisions

Decision making under uncertainty: the case of Middle East Gulf dry bulk shipping companies

This research focuses on middle management tactical decision-making under uncertainty in a highly volatile business/market environment. In particular, this research focuses on chartering managers in the dry bulk ship-owning and ship-operating companies in the Middle East Gulf region, while making their daily chartering decisions under uncertainty. Under the umbrella of bounded rationality, the approach of this research goes through the managerial psychology of the chartering managers in Middle East Gulf (MEG) shipping companies, and the effect of the heuristics and biases on their decisionmaking. Descriptive and normative approaches to decision making, heuristics, biases, dual process decision-making model, control over heuristics, analytical intervention, and explicit reasoning are the key concepts constructing this research's framework. The aim of this research is to design a ship-chartering decision-making model that can streamline chartering managers' decision-making process, assist MEG ship owners and operators in improving the value proposition for their ships while underway, and contributes to the enhancement of their efficiency. This research employs a mixed-methods approach, where both qualitative and quantitative techniques have been used to collect the required data. After applying suitable analyses' techniques, this document synthesizes the qualitative and quantitative findings to develop the components of the looked-for decision-making model. The findings of this research reveal the chartering managers' predominant decisions, the heuristics frequently used by chartering managers in MEG, the emanating biases in ship chartering decisions, and the task-related factors affecting the initial intuitive stage. The findings of this research also identify the factors affecting the top-down control over heuristics in ship chartering decisions in MEG dry bulk shipping companies, and the sources of the bottom-up control. Building on the work done by Jonathan Evans on dual process modeling, and the recent work done by Gordon Pennycook, Jonathan Fugelsang, and Derek J. Koehler on the three-stage dual process modeling, this research introduces a revised three-stage dual process decision-making model that is specifically designed for ship chartering decision-making in Middle East Gulf shipping companies

Gotta catch 'em all: Modeling All Discrete Alternatives for Industrial Energy System Transitions

Industrial decision-makers often base decisions on mathematical optimization models to achieve cost-efficient design solutions in energy transitions. However, since a model can only approximate reality, the optimal solution is not necessarily the best real-world energy system. Exploring near-optimal design spaces, e.g., by the Modeling All Alternatives (MAA) method, provides a more holistic view of decision alternatives beyond the cost-optimal solution. However, the MAA method misses out on discrete in-vestment decisions. Incorporating such discrete investment decisions is crucial when modeling industrial energy systems. Our work extends the MAA method by integrating discrete design decisions. We optimize the design and operation of an industrial energy system transformation using a mixed-integer linear program. First, we explore the continuous, near-optimal design space by applying the MAA method. Thereafter, we sample all discrete design alternatives from the continuous, near-optimal design space. In a case study, we apply our method to identify all near-optimal design alternatives of an industrial energy system. We find 128 near-optimal design alternatives where costs are allowed to increase to a maximum of one percent offering decision-makers more flexibility in their investment decisions. Our work enables the analysis of discrete design alternatives for industrial energy transitions and supports the decision-making process for investments in energy infrastructure.Comment: 6 pages, 2 figures, Annual International Conference of the German Operations Research Society (GOR) 202

Bayesian factor analysis for mixed data on management studies

Purpose Factor analysis is the most used tool in organizational research and its widespread use in scale validations contribute to decision-making in management. However, standard factor analysis is not always applied correctly mainly due to the misuse of ordinal data as interval data and the inadequacy of the former for classical factor analysis. The purpose of this paper is to present and apply the Bayesian factor analysis for mixed data (BFAMD) in the context of empirical using the Bayesian paradigm for the construction of scales. Design/methodology/approach Ignoring the categorical nature of some variables often used in management studies, as the popular Likert scale, may result in a model with false accuracy and possibly biased estimates. To address this issue, Quinn (2004) proposed a Bayesian factor analysis model for mixed data, which is capable of modeling ordinal (qualitative measure) and continuous data (quantitative measure) jointly and allows the inclusion of qualitative information through prior distributions for the parameters’ model. This model, adopted here, presents considering advantages and allows the estimation of the posterior distribution for the latent variables estimated, making the process of inference easier. Findings The results show that BFAMD is an effective approach for scale validation in management studies making both exploratory and confirmatory analyses possible for the estimated factors and also allowing the analysts to insert a priori information regardless of the sample size, either by using the credible intervals for Factor Loadings or by conducting specific hypotheses tests. The flexibility of the Bayesian approach presented is counterbalanced by the fact that the main estimates used in factor analysis as uniqueness and communalities commonly lose their usual interpretation due to the choice of using prior distributions. Originality/value Considering that the development of scales through factor analysis aims to contribute to appropriate decision-making in management and the increasing misuse of ordinal scales as interval in organizational studies, this proposal seems to be effective for mixed data analyses. The findings found here are not intended to be conclusive or limiting but offer a useful starting point from which further theoretical and empirical research of Bayesian factor analysis can be built

A cognitive process approach to modeling gap acceptance in overtaking

Driving automation holds significant potential for enhancing traffic safety. However, effectively handling interactions with human drivers in mixed traffic remains a challenging task. Several models exist that attempt to capture human behavior in traffic interactions, often focusing on gap acceptance. However, it is not clear how models of an individual driver's gap acceptance can be translated to dynamic human-AV interactions in the context of high-speed scenarios like overtaking. In this study, we address this issue by employing a cognitive process approach to describe the dynamic interactions by the oncoming vehicle during overtaking maneuvers. Our findings reveal that by incorporating an initial decision-making bias dependent on the initial velocity into existing drift-diffusion models, we can accurately describe the qualitative patterns of overtaking gap acceptance observed previously. Our results demonstrate the potential of the cognitive process approach in modeling human overtaking behavior when the oncoming vehicle is an AV. To this end, this study contributes to the development of effective strategies for ensuring safe and efficient overtaking interactions between human drivers and AVs

SELECTED ASPECTS OF MODELING THE PROCESS OF EVALUATING BUSINESS STRATEGIES FOR SUSTAINABLE ECONOMIC DEVELOPMENT OF IRON ORE ENTERPRISES

The theoretical principles of modeling the process of evaluation of business strategies for ensuring sustainable economic development of iron ore enterprises are considered in the article, taking into account the current state of the domestic economy. The basic model of the situation of making a rational decision concerning the problem of optimization of business strategies in the conditions of uncertainty and conflict of the market environment is defined, which is a generalized matrix of the problem of mathematical programming, the solution of which is the optimal parameters of a mixed strategy for managing the sustainable development of iron ore enterprise. The procedure of multicriteria game-theoretic evaluation of alternatives in the application of mathematical theory of conflict situations in the work is recommended to be carried out according to a certain algorithm, which reflects the sequence of stages of modeling the effective evaluations of individual business strategies when using the functionals of evaluation with negative, but continuous. In the work it is proved that not only research of their optimality but also issues related to forecasting a guaranteed positive positive result is of particular importance when forming situations of financial and economic substantiation and making management decisions regarding individual business strategies of the enterprise. As a result of using the proposed methodological approaches, this study achieves a scientifically sound isolation of certain key business processes of the enterprise's production and economic system in order to carry out more in-depth analysis of problematic business operations and to make adequate strategic decisions regarding the prospects of sustainable economic development of the iron ore enterprises.The theoretical principles of modeling the process of evaluation of business strategies for ensuring sustainable economic development of iron ore enterprises are considered in the article, taking into account the current state of the domestic economy. The basic model of the situation of making a rational decision concerning the problem of optimization of business strategies in the conditions of uncertainty and conflict of the market environment is defined, which is a generalized matrix of the problem of mathematical programming, the solution of which is the optimal parameters of a mixed strategy for managing the sustainable development of iron ore enterprise. The procedure of multicriteria game-theoretic evaluation of alternatives in the application of mathematical theory of conflict situations in the work is recommended to be carried out according to a certain algorithm, which reflects the sequence of stages of modeling the effective evaluations of individual business strategies when using the functionals of evaluation with negative, but continuous. In the work it is proved that not only research of their optimality but also issues related to forecasting a guaranteed positive positive result is of particular importance when forming situations of financial and economic substantiation and making management decisions regarding individual business strategies of the enterprise. As a result of using the proposed methodological approaches, this study achieves a scientifically sound isolation of certain key business processes of the enterprise's production and economic system in order to carry out more in-depth analysis of problematic business operations and to make adequate strategic decisions regarding the prospects of sustainable economic development of the iron ore enterprises