Spreadsheet-based Decision Support System Research Articles

Assessing the feasibility of gray, blue, and green ammonia productions in Indonesia: A techno-economic and environmental perspective

Ammonia, owing to its carbon-free attributes, stands as a promising alternative for replacing fossil-based fuels. This study investigates the techno-economic and environmental aspects of gray, blue, and green ammonia production in Indonesia. In this regard, a spreadsheet-based decision support system has been developed to analyze the levelized cost of each mode of ammonia production and their cost sensitivity across various parameters. The results of the analysis show a levelized cost of gray ammonia of $297 (USD) per ton, which is strongly affected by natural gas prices and carbon taxation. Blue ammonia emerges as the most stable production option with a levelized cost of $390 per ton, impacted by natural gas prices and the expenses associated with carbon sequestration. On the other hand, the levelized cost of green ammonia varies between $696 to $1,024 per ton and is predominantly influenced by the choice of electrolyzers, the cost of renewable energy sources, and maintenance and operational expenditures. Furthermore, the study reveals that gray and blue ammonia production result in emissions of 2.73 and 0.28 tons of CO2 equivalent per ton of ammonia, respectively, while in-situ carbon emissions from green ammonia can be considered negligible. Overall, this study underscores the potential of implementing green ammonia production utilizing geothermal or hydropower renewable energy resources as viable solutions for decarbonizing the power, industry, and transport sectors in Indonesia. Several policy recommendations aimed at overcoming existing barriers to the development of green ammonia plants in the country are also provided.

A spreadsheet-based decision support system for selection of optimal soil liquefaction mitigation technique

Improving constructability on soils susceptible to seismic induced liquefaction requires deployment of soil liquefaction mitigation technique (SLMT). However, selecting optimal SLMT with respect to applicable site and project constraints is an intricate task. This paper proposes a spreadsheet-based decision support system (SDSS) developed for retrieving set of specific mitigation requirements from the user and prescribe an optimal SLMT from a choice of multiple SLMT. This is achieved by extracting hindsight and data analytics on 14 SLMT(s) into a knowledge-based shell and processing it by a ‘Hybridized multi-criteria optimization’ algorithm. The competence of SDSS was assessed by analysing five case histories and then adjudging its decision analytics with respect to a devised acceptance criteria. As per the criteria, the optimal SLMT deduced for each case history was found to be rational on the grounds of feasibility and optimality. Hence, the developed SDSS could be foreseen as a novel, structured and a convenient proposition for optimal selection of soil liquefaction mitigation technique.

A spreadsheet-based decision support system for examination timetabling

Examination timetabling is an inevitable problem of educational institutions. Each institution has its own particular limitations; however, the main structure is the same: assigning exams to time slots and classrooms. Several institutions solve the problem manually, but it becomes more difficult every year with increasing numbers of students and limited resources. There are many studies in the literature addressing the examination timetabling problem ETP and providing high quality solutions within reasonable amounts of time. Nevertheless, almost none of them can be used in practice since they are not converted into a decision support system DSS . Commercial DSSs, on the other hand, are generally transactionally based and do not have optimization capabilities, i.e. they prevent conflicts via functional user interfaces. In this study, we propose a mixed integer programming MIP model that addresses the ETP of the Industrial Engineering Department of Yildiz Technical University. The model, which is capable of solving a wide range of similar ETP instances, is embedded into a DSS in the form of a spreadsheet. Given the enrollment lists of the courses, it generates schedules with minimum conflicts and consecutive exams while addressing requests of the lecturers and students. It does not require any technical knowledge and can be used by an average spreadsheet user. Moreover, it is flexible in terms of use for scheduling problems of other educational institutions. Currently, the DSS is in use by the department and real-life instances can be solved within a few seconds, saving significant amount of man-hours.

The Volkswagen Pre-Production Center Applies Operations Research to Optimize Capacity Scheduling

The Volkswagen Pre-Production Center (VPC) is responsible for the entire prototype assembly of the Volkswagen brand. In their assembly sites, however, they often cannot employ their manufacturing staff to the full utilization level, and therefore, the manufacturing volume is low. Maximizing the manufacturing volume for a given available capacity is a frequently pursued objective in industrial manufacturing. The planning task of capacity scheduling contributes to this objective by deciding on resource allocation and the selection and scheduling of orders. We were asked to evaluate possible operations research/management science (OR/MS) solutions for their capacity scheduling problem. To this end, we developed a prototype for capacity scheduling based on binary integer programming. After the prototype had revealed high improvement potential, we developed a spreadsheet-based decision support system (DSS) for daily capacity scheduling. The schedules generated by the DSS were substantially better than the solutions generated by the current manual procedure, in terms of both accomplished manufacturing volume and planning effort. After successful test implementation and rollout, the VPC estimated the annual cost savings to lie in the six-digit Euro range. Meanwhile, we continue spreading OR/MS methods to neighboring departments of the VPC.

Development of a Spreadsheet DSS for Multi-Response Taguchi Parameter Optimization Problems Using the TOPSIS, VIKOR, and GRA Methods

This paper presents a spreadsheet-based decision support system (DSS) for any parameter optimization problem, in the small- and medium-sized enterprises to help the managers to make better decisions. Microsoft Excel is used as a DSS development platform. The DSS application requires the quality characteristics and the level of parameters affecting the problem. The proposed system considers three multi-criteria decision-making methods: TOPSIS, VIKOR and GRA. These methods are integrated into the Taguchi method to convert the multi-response optimization problem to a single-response problem. The DSS suggests proper Taguchi experimental designs and provides the decision maker with an opportunity to use different metrics and to validate the experimental results. Several issues and an application are provided for illustrative purposes. The proposed DSS is tested on a case study (the performance of the mixed integer programming (MIP) formulation solver) and the results highlight that the system is capable of offering satisfactory outcomes. Using such a quick and flexible DSS might help to reduce the daily workload of the decision makers. The different metrics used for the response variables which results with the different parameter combination. Using the optimal parameter combination of TOPSIS (come to the fore in case MinBest metric used), the MIP formulation solver gives the best integer objective function value of 609 and a GAP value of 1.93%, both of which are less than the values obtained using the other methods. Using the optimal parameter combination of GRA (come to the fore in case OptBest metric used), the MIP formulation gives a best integer objective function value of 632 and a GAP value of 6.52%, both of which are less than the values obtained by using the other methods.

An open source decision support system for facility location analysis

This paper introduces FLP Spreadsheet Solver, an open source spreadsheet based Decision Support System for Facility Location Problems. Structure of the spreadsheets, interface of the solver, and a Tabu Search algorithm implemented within the solver are described. An integer programming formulation of the underlying facility location problem is provided. Computational tests show that FLP Spreadsheet Solver can solve benchmark p-median and capacitated p-median instances to near optimality. The paper also includes a case study consisting of the application of FLP Spreadsheet Solver to a healthcare facility location problem.

Sistema de apoio à decisão baseado em planilha eletrônica para otimização da programação de entrega de concreto pronto

Este artigo trata de um sistema de apoio à decisão (SAD) baseado em planilha eletrônica para o problema de programação das entregas de concreto produzido em centrais dosadoras, adequado à realidade brasileira. Tal programação engloba as decisões de qual central deverá atender cada cliente e em qual horário cada veículo de entrega deverá ser carregado nessa central, de forma a maximizar a receita marginal total do sistema. São consideradas restrições de capacidade de carregamento de veículos por central, disponibilidade da frota e garantia de atendimento, por uma única central, de todos os pedidos de cada cliente. A fim de resolver esse problema de otimização de maneira rápida e eficiente, é proposto um modelo de programação matemática baseado em uma rede espaço-tempo. O SAD em ambiente de planilha eletrônica, inédito na literatura, possibilita a sua utilização em uma empresa concreteira que opera diversas centrais dosadoras de concreto de maneira fácil e direta, por usuários sem conhecimentos de pesquisa operacional, sendo portanto adequado para empresas que não tem porte ou não estão preparadas para investir em sistemas corporativos de apoio à programação.

Development of a decision support system using Tabu Search algorithm for the warehouse layout problem

The warehouse layout problem involves allocation of different product types to certain areas of a warehouse so that the cost of material handling from docks of the warehouse can be minimized. In this study, a Tabu Search algorithm as a satisfying solution for the quadratic assignment problem is applied for modeling. The layout problem is linked to Visual Basic® programming in Excel®. A spreadsheet-based decision support system is developed in which the user specifies the area of the warehouse by height and number of bays, places the docks around the warehouse and gives the frequency of their usage, and provides the demand and area required per product type. Then, the problem is solved to find the proper location of each product type for minimal material handling cost. The proposed system will provide decision-makers and engineers with a suitable answer in negligible time.

Designing the spreadsheet-based decision support systems course: An application of Bloom's taxonomy

Decision support systems (DSS) have played an important role in organizations for many years. As DSS continue to be developed for industry applications, a number of business programs in universities offer a specialized course aimed at helping students better understand and develop DSS systems to support decision making. Spreadsheet software coupled with an application programming language can serve as a useful DSS generation software package for such courses. To help students develop their technical skills for spreadsheet-based DSS, the principles underlying Bloom's taxonomy of educational objectives can serve as a guiding framework for instructional design. This article describes how Bloom's taxonomy has been used to support the design of two different DSS courses, an undergraduate course and an MBA course. Student survey data collected over the past four years from students enrolled in nine sections of the DSS courses are reported. Based on the survey findings, as well as the instructor's observations, it appears that a teaching strategy based on Bloom's taxonomy offers a worthwhile framework for instructors who teach a spreadsheet-based DSS course.

A Player Selection Heuristic for a Sports League Draft

Sports leagues conduct new player entry drafts in which franchises select, in a pre-determined order, players to complement their existing rosters. We model the decision-making process of a single sports franchise during a player selection draft. The basic premise of our model is that a team selects a particular player based on a combination of the player's estimated value, the value of the other players currently available, and the team's need at each position. We first conceptualize a sports league draft using a stochastic dynamic program. However, this formulation is not directly solvable for practical-sized problems due to the overwhelming computational complexity. Therefore, we introduce additional assumptions and restrictions that result in a tractable deterministic dynamic program. We implement the model within a spreadsheet-based decision support system that allows the user to compute solutions under a variety of conditions. To benchmark our approach, we perform computational comparisons against several competing draft strategies in a series of simulated fantasy football drafts for the 2005 season. With perfect information regarding opposing teams' selections, our drafting strategy dominates these competing strategies. With imperfect information, there are draft instances in which our method is not guaranteed to dominate an alternate strategy; however, our drafting strategy outperforms the competing strategies on average and is more robust on the instances tested. Furthermore, we demonstrate that the decision-maker can incorporate information regarding the drafting behavior of opposing teams to improve the performance of our method.

Economic Analysis of an Irrigation System for Liquid Manure Application

Irrigation application of effluent from lagoon based systems is an important aspect of animal manure management in swine rearing facilities. This paper describes a procedure for obtaining least-cost components and operational parameters for an irrigation system used to apply liquid manure. The paper employs propositions from hydraulics—affinity laws and Hazen–Williams formula—to derive statistically estimable relationships between pressure, liquid output, power requirement, and impeller speed of an irrigation system. Coefficient estimates are then used in a spreadsheet based decision support system that employs an optimization program to select the least costly irrigation system. A practical application is showcased through simulation of three hypothetical swine farms. Main findings are that the use of this optimization procedure can result in cost savings for swine growers applying manure by irrigation and that the cost savings potentials increase with the farm size.

Validation of decision-aiding spreadsheets: the influence of contingency factors

This paper describes an investigation into the influence of contingency factors on the validation of spreadsheet-based decision support systems (DSS), and develops a methodological framework for validation that takes account of the effect of contingency factors. The research extends and confirms previous research by one of the authors who identified relevant contingency factors. The perceived influence of these contingency factors on validation effort was investigated by an empirical study, and the results of this study were then used to derive contingency-related guidance for validation. This was evaluated by a sample of practitioners and academics with experience in the development of spreadsheet-based DSS, and was then incorporated into a methodological framework for validation. The framework is designed to enable managers, decision-makers, project leaders and other non-OR specialists to identify the extent of validation effort likely to be required to ensure that the spreadsheet models that they build are valid. The research has implications for the validation of other types of OR models.

Bad numbers: coping with flawed decision support

Evidence is accumulating that many spreadsheet-based decision support systems contain errors. These errors can result in bad numbers, which in turn could lead to bad decisions. We review the literature on the origins and consequences of bad (erroneous) numbers produced by models and/or decision support systems built around them. Then, we present a case study in which an experiment in visual support for a sequential decision-making task was tainted by bad numbers. Both the literature review and the experiment indicate a robust human ability to overcome flawed decision support. We conclude with questions that need to be addressed in order to better understand the capabilities of humans to deal with erroneous results from decision support systems.

AMCIS 2002 Panels and Workshops II: Spreadsheet-Based DSS Curriculum Issues

When challenged to justify the value of information systems (IS) research, decision support systems (DSS) is usually cited as one the most compelling examples of where IS research made the transition successfully from theoretical academic journals into the “real-world”. In light of this assessment, it is somewhat surprising that offerings of DSS courses waned over the years. This paper identifies several possible reasons for the decline in DSS course offerings and suggests innovative approaches using spreadsheets for breathing new-life into this cornerstone of the IS field.

A spreadsheet-based decision support system for wood panel manufacturing

Wood paneling manufacturers face a number of complex decisions when trying to allocate production resources and combine various raw materials to meet production goals. While various linear programming formulations for this problem have been proposed, these models are often difficult to use and maintain for real-time decision making in a dynamic shop floor environment. This paper describes an MS Excel-based decision support system for wood panel manufacturing. The system is easy to use and maintain yet gives shop floor personnel access to powerful optimization capabilities useful for fine-tuning production processes in the face of changing supply and price situations.

A survey of contingency factors affecting the validation of end-user spreadsheet-based decision support systems

Decision support systems have become widespread in recent years. However, most of these systems are not carefully validated and this has led in some cases to serious errors. One of the principal reasons for the lack of validity is the lack of an operationalised validation methodology. A simplified validity framework has already been developed by the authors as the first part of a 3-phase approach towards devising a practical validation methodology. This paper describes the second phase, reporting as it does on a survey that has been undertaken to unearth the contingency factors that influence how the process of validation, employing the validity framework, will be carried out for a particular kind of decision support system—one involving a spreadsheet model.

A Survey of Contingency Factors Affecting the Validation of End-User Spreadsheet-Based Decision Support Systems

A Survey of Contingency Factors Affecting the Validation of End-User Spreadsheet-Based Decision Support Systems

Technoeconomic assessment of biomass to energy

A spreadsheet-based decision support system has been developed that allows easy evaluation of integrated biomass to electricity and biomass to ethanol systems. The Bioenergy Assessment Model (BEAM) has been developed to allow the techno-economic assessment of biomass to electricity and biomass to ethanol schemes, including investigation of the interfacing issues. Technical and economic parameters can be assessed for a variety of feedstocks, conversion technologies and generating cycles. A spreadsheet format has been used to make the model inherently expandable: new system options can be added by adding new spreadsheets and making minor adjustments to the executive program that links the spreadsheets together. Production modules are currently available for biomass supply from short rotation coppice and conventional forestry relevant to conditions and practices in NW Europe. The biomass conversion modules include pre-treatment (reception, storage, handling, comminution, screening and drying); atmospheric gasification (generic gasifier, wet gas scrubbing, dual fuel engine); pressure gasification (generic gasifier, hot gas filtration, gas turbine combined cycle); fast pyrolysis for liquid bio-fuel-oil (pyrolyser, oil storage, pilot-injected diesel engine); combustion (fluid bed combuster steam turbine), conventional acid hydrolysis fermentation and the NREL SSF process to ethanol. In addition there is a further module which can be used to examine the collection, mass burn and generation of electricity from MSW. BEAM has been used, and the results presented in this paper, to determine the costs of generating bio-electricity from short rotation coppice and conventional forestry over a range of power outputs and for each conversion technology. Alternative feedstock supply strategies have been examined and relations drawn between delivered feedstock cost and cost of electricity. Sensitivity analysis reveals that the cost of bio-electricity production from short rotation coppice is highly sensitive to the yield of the crop. BEAM has been shown to work well with the systems under consideration and is capable of further development. The long term aim is to provide a simple model with on-line help and information that will allow biomass systems developers to make initial assessments of the feedstock and technology options that are available and to direct research and development towards the more promising areas.

Allocation and routing of mobile computed tomography equipment

We consider the problem of allocating and routing mobile medical equipment to hospitals, as faced by an equipment leasing company. The equipment is leased to hospitals across the United States for periods ranging from a few weeks to many months. The problem is to satisfy the requirements of hospitals with different demand schedules given the equipment available. The objective is to maximize total revenues generated less the transportation costs incurred. The problem is here modeled as a network flow formulation. A spreadsheet-based decision support system was developed and implemented in a firm with no expertise or prior experience in such modeling efforts. Details of the system and its implementation are provided.

PASIM: A spreadsheet-based decision support system for performance analysis of production workers

Abstract Electronic spreadsheets offer low cost approach to information management and implementation of decision models for online decision support systems. In this paper, we have combined quantitative models, database management, and simulation to develop a decision support system for real-time performance monitoring of production workers.