Operations Research Techniques Research Articles

The application of operation research in the design of on-site construction organization

This article explores the integration of Operations Research (OR) principles in the design and management of on-site construction organizations. The first section introduces Operations Research as a multidisciplinary field that employs mathematical modelling, statistical analysis, and optimization techniques to enhance decision-making processes across various sectors. Key aspects such as mathematical modelling, optimization, decision analysis, simulation, queueing theory, linear programming, and game theory are highlighted. The second section focuses on the design of on-site construction organizations, emphasizing the structure and organization of resources, personnel, and processes essential for efficient project execution. Various key elements, including project management, site personnel, project support teams, engineering and design teams, health and safety personnel, procurement and supply chain, communication and coordination, equipment and maintenance, and environmental compliance, are discussed. The third section delves into the application of Operations Research techniques in the design and management of on-site construction organizations. It outlines how OR principles can be employed for resource allocation and optimization, project scheduling and planning, inventory management, equipment utilization, project costing and budgeting, risk management, supply chain management, human resource management, facility layout and design, and the development of decision support systems. The conclusion highlights that the strategic application of Operations Research methodologies contributes to enhanced efficiency, optimized resources, and improved decision-making throughout the construction project lifecycle. The integration of OR principles not only enhance the overall effectiveness of on-site construction organizations but also leads to cost savings, timely project completion, and improved project outcomes. As construction projects continue to grow in scale and complexity, the systematic and analytical approach provided by Operations Research becomes increasingly valuable in addressing the intricate challenges faced by construction stakeholders.

An adaptive large neighborhood search for the order picking process: the case of a retail distribution company in Italy

Order picking is one of the most important activities in warehouse management. By optimising the picking process, warehouse operations can be managed efficiently in terms of both time and logistics costs. In this work we apply operations research techniques to support the order picking process of an Italian retail distribution company. The picking process poses several challenges from an optimisation point of view, and the related optimization problems are very complex. Therefore, we define an Adaptive Large Neighbourhood Search (ALNS) algorithm that heuristically solves the problem. The proposed metaheuristic is tested on a set of 101 real orders processed by the company within one day. The computational experiments show that the ALNS shows good performances in terms of effectiveness, compared to the optimal solution, as well as allows to implement a better organisation of the order picking process than the one currently adopted by the company.

Discrete‐event simulation is still alive and strong: evidence from bibliometric performance evaluation of research during COVID‐19 global health pandemic

AbstractDuring the Annual Operational Research Society Simulation Workshop in Worchester, UK, in 2010, a panel discussion entitled “discrete‐event simulation (DES) is dead, long live agent‐based simulation (ABS)!” was held. Subsequent debates on the topic have captured the interest of many simulation professionals and researchers. This study lends credence to the discourse with evidence. In January 2020, a global health crisis named coronavirus disease (COVID‐19) occurred, infecting and killing millions of people globally, leading to community lockdowns and travel restrictions, and bringing the world to a standstill. Scientists scrambled for quick, practical solutions to stem the tide. Operational research (OR) and management science (MS) techniques, including modeling and simulation, provide effective methods to make COVID‐19 infection forecasts, assign/optimize intensive care unit beds, initiate healthcare management/control strategies, and decision‐making. The global pandemic problems offer an opportunity to evaluate the discourse on DES's continuous relevance and potency as an OR/MS technique. Utilizing bibliometric performance evaluation and text analytics of publications addressing various COVID‐19 pandemic problems, the results show an extensive use, relevance, and impact of the DES technique across multidisciplinary domains, including medical/healthcare, social and behavioral sciences, business, molecular biosciences, and more. The intellectual structure highlights strong multidisciplinary collaboration among sources in decision sciences, healthcare, natural, behavioral, and social sciences. The social network analysis of the publications shows the contributions and collaborations among authors, institutions, and countries. The study demonstrates that DES is still alive and robust, notwithstanding the hype about ABS.

Proactive berth scheduling with data‐driven buffer time in container terminals

AbstractGlobal shipment volumes have been increasing due to changes in the business environment of e‐commerce and manufacturing. Consequently, container vessels carry more cargo for international trade, increasing uncertainties in terminal management. Terminal operators manage terminals by establishing a proactive schedule that responds to disruptions such as vessel delays, and the introduction of buffer time is a representative proactive strategy. In this study, by analyzing historical delay data with machine learning, we propose data‐driven buffer times to consider the heterogeneous arrival uncertainty of vessels. Thus, we proactive scheduling with data‐driven buffer times according to the desired robustness levels. This is a novel study on berth scheduling that applies data mining approaches to improve operations research techniques. Numerical experiments were conducted on the berth scheduling with time‐invariant quay crane assignment using real‐life data to validate the effectiveness of the proposed method. These experimental results revealed that applying the data‐driven buffer time could effectively reduce the cost incurred at the terminal by balancing baseline and recovery costs. In addition, our proposed methodology ensured the quality of the solution compared with a stochastic method and reduced the computational burden of a stochastic problem by using the data‐driven buffer times obtained prior to the solution construction. Therefore, the proposed method can be introduced into terminal operations to overcome the deficiencies of traditional approaches in terms of academic perspective.

A Multi-Stage Approach for External Trucks and Yard Cranes Scheduling with CO2 Emissions Considerations in Container Terminals

Background: In container terminals, optimizing the scheduling of external trucks and yard cranes is crucial as it directly impacts the truck turnaround time, which is one of the most critical performance measures. Furthermore, proper scheduling of external trucks contributes to reducing CO2 emissions. Methods: This paper proposes a new approach based on a mixed integer programming model to schedule external trucks and yard cranes with the objective of minimizing CO2 emissions and reducing truck turnaround time, the gap between trucking companies’ preferred arrival time and appointed time, and the energy consumption of yard cranes. The proposed approach combines data analysis and operations research techniques. Specifically, it employs a K-means clustering algorithm to reduce the number of necessary truck trips for container handling. Additionally, a two-stage mathematical model is applied. The first stage employs a bi-objective mathematical model to plan the arrival of external trucks at the terminal gates. The second stage involves a mathematical model that schedules yard cranes’ movements between different yard blocks. Results: The results show that implementing this methodology in a hypothetical case study may lead to a substantial daily reduction of approximately 31% in CO2 emissions. Additionally, the results provide valuable insights into the trade-off between satisfying the trucking companies’ preferred arrival time and the total turnaround time. Conclusions: The integration of data clustering with mathematical modeling demonstrates a notable reduction in emissions, underscoring the viability of this strategy in promoting sustainability in port-related activities.

The Application of Information Systems to Improve Ambulance Response Times in the UK

Emergency ambulance services in the UK are tasked with providing pre-hospital patient care and clinical services with a target response time between call connect to on-scene attendance. In 2017, NHS England introduced four new response time categories based on patient needs. The most challenging is to be on-scene for a life-threatening situation within seven minutes of the call being connected when such calls are random in terms of time and place throughout a large territory. Recent evidence indicates emergency ambulance services regularly fall short of achieving the target ambulance response times set by the National Health Service (NHS). To achieve these targets, they need to undertake transformational change and apply statistical, operations research and artificial intelligence techniques in the form of five separate modules covering demand forecasting, plus locate, allocate, dispatch, monitoring and re-deployment of resources. These modules should be linked in real-time employing a data warehouse to minimise computational data and generate accurate, meaningful and timely decisions ensuring patients receive an appropriate and timely response. A simulation covering a limited geographical area, time and operational data concluded that this form of integration of the five modules provides accurate and timely data upon which to make decisions that effectively improve ambulance response times.

Applications Of Operations Research in Various Fields

Operations research uses techniques from a variety of disciplines, including mathematics, statistics, economics, engineering etc. A mathematical model of the real time problem can be formulated by Operations research techniques. These models help to predict future behaviour of the systems, changes in the system or in the methods of operations. This Paper discusses about the applications of Operations research in different field.

Guest editorial: Operational research techniques and statistical learning for textile industry: look forward

Guest editorial: Operational research techniques and statistical learning for textile industry: look forward

Project Planning Application to Juice Production Using PERT/CPM Technique: A Case Study

Timely delivery of natural and fresh juice to its’ growing customers is the focus of SCUBED 100%. The CPM (Critical Path Method) and PERT (Program Evaluation and Review Technique) techniques were applied in minimizing the expected time duration for juice production at SCUBED 100%. The current expected production time for a batch stood at 656.66 minutes. Modifications were made on the initial model to minimize the expected duration and after two modification processes, an estimated time duration of 458.33 minutes was realized, saving 198.33 minutes (about 3.3 hours) of production time. This study encapsulates the interplay of theoretical insights and practical implementation, confirming the potential of operational research and management techniques in designing real-world outcomes. SCUBED 100%'s journey towards operational excellence demonstrates the transformative potential of time optimization.

Analytics-driven complaint prioritisation via deep learning and multicriteria decision-making

Complaint analysis is an essential business analytics application because complaints have a strong influence on customer satisfaction (CSAT). However, the process of categorising and prioritising complaints manually can be extremely time consuming for large companies. In this paper, we propose a framework for automatic complaint labelling and prioritisation using text analytics and operational research techniques. The labelling step of the training set is performed using a simple weighting approach from the multiple-criteria decision-making (MCDM) literature, while transformer-based deep learning (DL) techniques are used for text classification. We define two priority classes, namely, urgent complaints and other claims, and develop a system for automatic complaint categorisation. Our experimental results show that excellent predictive performance can be achieved with state-of-the-art text classification models. In particular, BETO, a bidirectional encoder representations from transformers (BERT) model trained on a large Spanish corpus, reaches an accuracy (ACCU) and area under the curve (AUC) of 92.1% and 0.9785, respectively. This positive result translates into a successful complaint prioritisation scheme, which improves CSAT and reduces the churn rate.

EFFICIENT MANAGEMENT OF PHARMACY OPERATIONS THROUGH OPERATIONS RESEARCH TECHNIQUES

This article discusses the use of operations research techniques to improve the management of pharmacy operations. In the context of Pharmacy Management Information Systems, some of the OR techniques that could be used are: Linear Programming (LP), Queueing Theory, Simulation, Decision Analysis, Forecasting, Network Analysis. The aim of applying operations research is to make it easier for pharmacy owners to manage their businesses by streamlining the process through the use of mathematical and quantitative methods. Operations Research (OR) is a problem-solving approach that involves analyzing and optimizing complex systems. In the context of Pharmacy Management Information Systems (PMIS), the study covers a wide range of areas such as sales inventory, stocks inventory, purchases (orders, receipts), payroll, accounting, financial management, sales reports (daily, monthly, yearly), and the pharmacy prescription book (for senior citizens and persons with disabilities). Additionally, a point of sale (POS) system has been built into the application, which can be used in both single and multi-user environments. The Pharmacy Automate or PMIS is a Windows-based operating system that can significantly improve pharmacy business operations by automating the entire process and helping owners keep track of their inventory and other important aspects of the business. The use of OR techniques has proven to be very useful in the more complex fields of pharmacy business operations.

Using DEMATEL and ISM for Designing Green Public Policies Based on the System of Systems Approach

In this paper, we propose a novel approach to the development of green public policies. We emphasize the significance of the system of systems (SoSs) methodology, which concentrates on understanding and managing complex systems by contemplating their interdependencies and interactions as a single integrated system. Based on this perspective, we consider green public policy as a system interacting with the energy, health, pollutants, and economic systems of the SoSs. As a method of systematic structural analysis, we use both decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques to understand the relationships between the systems listed above. We provide a literature review on the application of these soft operation research (SOR) techniques. We note that SOR methods are suitable for the formulation of effective public policies. Using an example, we demonstrate the primary advantage of DEMATEL and ISM, which is the establishment of easily comprehendible causal relationships between the systems in the SoSs.

ENHANCING LIVESTOCK MANAGEMENT EFFICIENCY THROUGH OPERATIONS RESEARCH: ADVANCEMENTS IN FEED FORMULATION, GENETIC OPTIMIZATION, AND DISEASE CONTROL

This research paper explores the applications of Operations Research (OR) techniques in livestock management, specifically focusing on feed formulation and diet optimization, livestock breeding and genetic optimization, and disease control and vaccination scheduling. The study employs a systematic methodology that integrates mathematical modeling, optimization algorithms, and data analysis to address the challenges and objectives in each area. A literature review reveals the effectiveness of OR in optimizing feed formulations, genetic selection strategies, and vaccination scheduling, leading to improved animal nutrition, productivity, and disease control. The findings highlight the value of OR techniques in enhancing decision-making and promoting sustainable and efficient practices in livestock management. However, practical challenges related to data availability and stakeholder acceptance need to be addressed for widespread implementation. This research contributes to the understanding of the applications of OR in livestock management and provides a foundation for future research and practical implementation in the industry.

Special Issue of INFORMS Journal on Computing—Quantum Computing and Operations Research

Free AccessAboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to SectionFree Access HomeINFORMS Journal on ComputingAhead of Print Special Issue of INFORMS Journal on Computing—Quantum Computing and Operations ResearchCarleton Coffrin, Elisabeth Lobe, Giacomo Nannicini, Ojas ParekhCarleton Coffrin, Elisabeth Lobe, Giacomo Nannicini, Ojas ParekhPublished Online:15 May 2023https://doi.org/10.1287/ijoc.2023.cfp.v35.n3IntroductionQuantum computers offer an alternative way to approach computational problems, and it is widely believed that they can solve certain tasks significantly faster or with greater accuracy than any classical (i.e., nonquantum) computer. The impact of quantum computers on operations research, and vice versa, has thus far been limited, but this is expected to change. Indeed, the construction of more refined and scalable quantum hardware and software calls for the solution of a diverse range of problems that operations researchers are in prime position to address; examples include hardware design, hardware control, compiling, scheduling, and classical simulation of quantum devices. Furthermore, because of tremendous progress in hardware development and in the construction of basic algorithmic primitives, the last few years have shown significant growth in the volume of research dedicated to the application of quantum computers for the solution of operations research problems. This includes, but is not limited to, optimization, simulation, and learning.Special Issue ScopeThe INFORMS Journal of Computing wishes to promote high-quality research at the intersection of quantum computing and operations research. To foster the growth of the community and give visibility to top-tier work in this area, the Journal is devoting a special issue to this topic, and it invites authors to submit manuscripts that substantially advance the state of the art in methodology, theory, algorithms, applications, or software implementation as they pertain to all areas at the intersection of quantum computing and operations research. This includes, but is not limited to, novel results regarding the development and analysis of quantum or quantum-inspired classical algorithms for solving problems in operations research or based on the application of operations research techniques, the development of solution methodologies for problems that arise in the design and operation of quantum computers, and insightful empirical testing of the aforementioned types of algorithms.The main goal of this special issue is to give a platform to novel research in this emerging area. Survey and tutorial papers are included in this call; however, any survey or tutorial paper will have to maintain a very high standard of novelty and contribution with respect to existing surveys and tutorials in the open literature. We strongly encourage interested authors to contact one of the guest editors for this issue to discuss whether their work fits the scope of this special issue (see Timeline).The editorial statement of the journal is available at https://pubsonline.informs.org/page/ijoc/editorial-statement.Submissions should follow the standard requirements of the INFORMS Journal on Computing articles available at https://pubsonline.informs.org/page/ijoc/submission-guidelines.Please note that the INFORMS Journal on Computing has a data policy https://pubsonline.informs.org/page/ijoc/datapolicy and a software policy https://pubsonline.informs.org/page/ijoc/softwarepolicy.TimelineThe editors ask potential authors to prepare a short proposal, that is, a letter of intent, before making a full submission of a paper. Please note the following dates:September 30, 2023: Letter of interest sent to the editors (via email), with an abstract for the proposed contribution. (This step is not mandatory but strongly preferred to ensure proper review. Early letters are encouraged; submit the letter copying all guest editors).January 15, 2024: Deadline for first round of submissions.April 15, 2024: First round of reviews completed; decisions (and requests for revision, if appropriate) delivered to authors.June 15, 2024: Revisions due after first round decisions.August 15, 2024: Second round of reviews delivered to authors.August 30, 2024: Final versions of accepted papers must be submitted.Submission InstructionsPapers must be submitted online at https://mc.manuscriptcentral.com/ijoc.When submitting a paper, please note the following:Under “Step 1: Type, Title, & Abstract,”- select “Special Issue” for “Type,”- select “Special Issue” under “Select topic area of submission,”- and answer “Quantum Computing” for “If this paper is for a special issue, which one is it for?”. Back to Top Next FiguresReferencesRelatedInformation Articles In Advance Article Information Metrics Information Published Online:May 15, 2023 Copyright © 2023, INFORMSCite asCarleton Coffrin, Elisabeth Lobe, Giacomo Nannicini, Ojas Parekh (2023) Special Issue of INFORMS Journal on Computing—Quantum Computing and Operations Research. INFORMS Journal on Computing 0(0). https://doi.org/10.1287/ijoc.2023.cfp.v35.n3 PDF download

Use of operational research techniques for concrete mix design: A systematic review

Traditional methods for designing concrete mixtures provide good results; however, they do not guarantee the optimum composition. Consequently, applying operational research techniques is motivated by an increasing need for designers to proportion the concrete's raw materials that satisfy the concrete performance requirements such as mechanical properties, chemical properties, workability, sustainability, and cost. For this reason, many authors have been looking for mathematical programming and machine learning solutions to predict concrete mix properties and optimise concrete mixtures. Therefore, a comprehensive review of operational research techniques concerning the design and proportioning of concrete mixtures and a classification framework are presented herein.

Relevance of Project Evaluation and Review Technique (PERT) for Procurement of Equipments in a Government Medical College and Hospital in North-East India

Introduction: Continuous procurement of various equipments in the hospitals is essential to keep up with global progress of healthcare services. In public sectors, procurement process largely depends on budget sanctions and also by a number of formal procedures and rules which leads to delayed procurement. With this prevalent scenario, the present study was carried out to evaluate the procurement of two major equipments in an apex tertiary care institute using Project Evaluation and Review Technique (PERT). Objective: This study was done to evaluate the procurement of two major equipments using PERT in a tertiary care institute. Method: This study was conducted using Operational Research technique in an apex tertiary care institute i.e., medical college and hospital, in one of the North Eastern states of India. All the procurements related to equipments in that teaching hospital initiated in the financial year 2021 were listed. Out of them, two procurement files were selected by simple random sampling; procurement of Operating Table and Bio Safety cabinet Level – III. Project Evaluation and Review Technique (PERT) was applied to calculate the possible reduction in time in the whole procurement process. Results: The present study showed that procurement of Operating table took 185 days where minimum 8 days could have been saved and procurement of Bio-Safety cabinet Level-III was completed by 702 days where minimum 196 days could have been saved. Conclusion: Application of PERT in this procurement evaluation process can play significant role by calculating critical path and predicting the possible delay.

Simplex method for profit maximization in Chinese breakfast food stall

Linear programming is an operational research technique widely used to identify action solutions for managers. The linear programming model explores the efficient use of available raw materials to produce different marketable products. Linear programming will encourage companies to increase production by taking full advantage of this opportunity. However, the trial-and-error approach is most often used by many organizations. As a result, firms find it challenging to allocate scarce resources in a profit-maximizing manner. This study focuses on implementing optimization principles to optimize manufacturing revenues through linear programming to measure production costs and determine their optimal benefits. The study uses data from Chinese food stall reports for five breakfast types: nasi lemak, fritters, curry puff, ear-eye cake, and popiah. The attribute has been identified as a linear programming problem, built mathematically and solved using Excel software. The results show that the food stall should concentrate more on producing curry puff and popiah. In comparison, other products should be produced less because their value becomes zero to reach the maximum monthly profit of RM28, 236. The analysis found that curry puff and popiah objectively contribute to the revenue. Therefore, more curry puff and popiah must be produced and sold to maximize profit.

A Review Study on Optimizing Inventory Management through Operations Research Techniques

A Review Study on Optimizing Inventory Management through Operations Research Techniques

Operations Research to Solve Kidney Allocation Problems: A Systematic Review

Operations research techniques enable health care administrators to optimize resource allocation and to find solutions to staff and patient scheduling problems. We aimed to conduct the first systematic review of the international literature on the use of operations research for allocating deceased-donor kidneys. We searched the MEDLINE, EMBASE, and PubMed databases from inception to February 2023. Two reviewers independently screened the title/abstract and subsequently the full text of potentially eligible articles and abstracted the data. Quality assessment of the final set of studies was conducted using Subben's checklist. Of the 302 citations identified, 5 studies were included. These studies covered three themes, including (1) provider-facing decision aids to determine the timing of transplant for single or multiple patients; (2) system-level planning on kidney allocation based on blood type matching rules; and (3) patient-facilitated wait times estimation using incomplete information. Markov models, sequential stochastic assignment models, and queuing models were amongst the most used techniques. Although we found all included studies to meet Subben's criteria, we believe the checklist in its current form lacks items to assess the validity of model inferences. As such, we ended this review with a set of practical recommendations. Our review demonstrated the utility of operations research techniques in assisting the system, healthcare providers, and patients in the transplantation process. More research is needed to reach a consensus on a model that can be used to support the decision-making of different stakeholders for efficient kidney allocation, with the ultimate goal of reducing the gap between kidney supply and demand and enhancing the population's well-being.

Design of service network for containerized export by multimodal transportation: with quality concept

PurposeThe first purpose is to assess the quality of containerized multimodal export and the second is to develop and demonstrate the design of a service network with quality approach.Design/methodology/approachThe article used the structural equation model to develop a model to measure the quality of multimodal transportation for containerized exports and finalized the model with an alternative approach. The evolutionary algorithm had been used to design a service network based on quality.FindingsProvided factors affecting quality of multimodal transportation and reverse to one hypothesis, the construct variation in cost, time shape and quantity did not affect the quality of multimodal transportation for containerized exports. The model without variation construct was finalized by exploring causality.Research limitations/implicationsThis research had scope till container loading onto the vessel and assessed the quality for containerized cargo only, and second research purpose is limited by assumed values of fitness function and the limited number of nodes, in service network design demonstration.Practical implicationsThis research provided a tool to measure the quality of multimodal transportation for containerized exports and demonstrated the field application of the model developed in service network design. This approach included all factors applicable across the container movement. The integrated approach of the article provided an organized method to design a service network for containerized exports.Originality/valueThis work provided the tool to assess the quality of multimodal transportation for containerized exports and developed an approach to design a service network of multimodal transportation based on quality. This approach has considered the factors of multimodal transportation comprehensively in contrast to the optimization approaches based on operation research techniques.