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Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cheirodon interruptus is a small characid widely distributed in South America; it is the species most commercialized as a baitfish in the Pampean region. Harvesting wild fish to supply a market of about two million people exerts a significant impact on fish assemblage and the environment. In search of alternatives to reduce the harvesting impact, growth and time to reach commercial fish size were analyzed and linked to consumer demand to design a strategy for production optimization. Based on the Akaike selection criteria, the use of the logistic model is proposed to estimate growth in C. interruptus aquaculture management. A differential growth by sex was observed, with females reaching a larger final size and males showing higher growth rates. These characteristics are useful to meet demand, optimizing time and space in the production schedule. The combined sequence of growth models and the demand curve show that a total of 5 induced spawning events are necessary to guarantee supply during peak seasonal demand. The results of this study can help to replace current fishing on wild fish populations, contributing to the regulatory frameworks in force and, hence, preventing degradation in fragile Pampean wetlands and aiding their recovery. [ABSTRACT FROM AUTHOR]

Extraction and development sequences must be scheduled strategically in order to maximize the life of mine. The complexities and computational difficulties associated with underground mine planning makes it challenging and open to further research. This paper presents a mathematical programming framework based on mixed-integer linear programming (MILP) formulation for integrated open stope development and production scheduling. Additionally, the MILP model incorporates backfilling, operational levels control, and stope extraction duration control during production scheduling. The MILP model generated a net present value of $244.7 M and determined the capital, ventilation, operational, and ore pass development schedules as well as mining and processing schedules for a gold project with 25 years mine life. A total of 2.48 Mt of material was extracted and processed out of 2.88 Mt mineralized material. [ABSTRACT FROM AUTHOR]

Planning, scheduling and delivery of shipments in workshops and factories active in the field of custom manufacturing industries are two important arms in the decision-making process that are used to optimize or reduce the adverse effects of problems in production, so this is one of the important pillars within any company or manufacturing plant. The importance of this issue will become clear when this tool is used in the real world and the production platform to benefit the companies. In this research, we will investigate a medium-term period and a short-term schedule for the production of carton sheets in the printing and packaging industry, and provide a method for separating cutting and scheduling models, as well as an innovative method for the scheduling. The result of the research is the comparison of the proposed method with the common method used in the factory to measure the efficiency.

Copyright of Journal High School is the property of ECORFAN-Mexico S.C. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In today's competitive environment, having the best sequence of operations for production and distribution activities is a basic need for survival. As a result, one of the major challenges in fixed supply chain systems is unnecessary transportation costs and the inability to meet customer demand as quickly as possible. In order to meet these challenges, factories and mobile equipment have been considered in this study, and have recently been used in several industries, including pharmaceutical, chemical, and dairy. In the course of this study, a novel mathematical model was put forward for an integrated production and distribution scheduling problem taking into account some real-world features, focusing on reducing customer waiting time and also reducing production costs. A small-scale problem was resolved to check the model's accuracy. The accuracy of the model is affirmed given the example and its solution acquired from GAMS software. The results of the study prove the effectiveness of this model in reducing customer waiting time and production costs and also demonstrate that the model has the capacity to be utilized by all organizations that produce and distribute perishable products, including dairy and pharmaceutical products, chemical compounds and masks during the Coronavirus pandemic. [ABSTRACT FROM AUTHOR]

With the liberalisation of the rail freight market, the number of railway undertakings in operation is increasing. Trains run by several railway undertakings (RUs) converge at industrial lines leading up to terminals. Here, uncoordinated interaction between mainline RUs and limited infrastructure capacity leads to bottlenecks, which reduces resource utilisation of railway undertakings. Outsourcing last-mile operations to an independent local railway undertaking can improve capacity utilisation and decrease the time engines of mainline engines spend within the considered network. In this paper, we propose the Industrial Line Scheduling Problem with multiple RU, a resource scheduling model for freight trains at industrial lines. The aim is to minimise unproductive time of mainline engines and the number of deployed local engines. The results show that the potential savings per employed local engine are highly dependent the timetables of inbound and outbound trains within the network, the dwell time of railcars and on the degree of local railway undertaking involvement. • Definition of Industrial Line Scheduling Problem with multiple Railway Undertakings • Introduction of a local RU handling shunting operations for multiple mainline RUs • Model formulation minimising mainline engine time and deployed local engines • Model demonstration on a real-life rail network and assessment of local RU influence [ABSTRACT FROM AUTHOR]

A dynamic optimization method was created to address the production schedule issue in an open-pit coal mine while taking into account the characteristics of the fuzzy structured element. The fuzzy mining capacities of all “geologically optimal push-back bodies” were then examined using the moving cove method. One of the most crucial elements in the process of open-pit coal mine production scheduling optimization is coal pricing. As a result, this work also presents a dynamic optimization technique for production scheduling that incorporates the prediction of economic time series and the generation of dynamic economic indices. An appropriate time series model is created to forecast the future coal price based on previous data on coal prices. The prediction results are used in the calculation of optimal mining body generation to dynamically obtain the optimal production scheduling model. The Baorixile Open-pit Coal Mine in China’s Inner Mongolia Autonomous Region is using this method. The Autoregressive Integrated Moving Average Model ARIMA is constructed to anticipate the coal price in the future 23 years by evaluating and processing the coal price from 2009 to 2022, and the ideal production scheduling scheme of the mine economics is afterwards identified. The ideal fuzzy coal mining volume, the potential production life, and the fuzzy total net present value (NPV) of the annual production scheduling are all provided at the same time. The optimization findings can better give fundamental support for mine design and future production since the fuzzy problem is accurately expressed by correct formulations.

Planning, scheduling and delivery of shipments in workshops and factories active in the field of custom manufacturing industries are two important arms in the decision-making process that are used to optimize or reduce the adverse effects of problems in production, so this is one of the important pillars within any company or manufacturing plant. The importance of this issue will become clear when this tool is used in the real world and the production platform to benefit the companies. In this research, we will investigate a medium-term period and a short-term schedule for the production of carton sheets in the printing and packaging industry, and provide a method for separating cutting and scheduling models, as well as an innovative method for the scheduling. The result of the research is the comparison of the proposed method with the common method used in the factory to measure the efficiency. [ABSTRACT FROM AUTHOR]

Faced with several challenges in the context of global competitiveness, the ferrous metal smelting industry seeks measures to reduce the costs of its internal processes. In this work, through the study of a mathematical model related to the optimization of productive processes, it is sought to help the companies in tactical-operational decision making and, consequently, to obtain reduction of production costs. This study aims at minimizing the cost function by minimizing the penalties involved in the process, to better serve the order book. These penalties refer to delays and anticipations of alloy mergers as well as penalties for furnace preparation. The model developed for small businesses is a multiperiod structured linear programming mixed, solved through programming in MatLab. The model proved to be satisfactory in terms of meeting the proposed objectives, reducing the total cost of the programming (this cost refers to the predefined value for the conditions of: keeping items in stock, delaying items in manufacturing, switching between different alloys in sequential loads). According to the simulations of conditions, up to 91% of the total cost reduction was obtained, which could not be verified previously through manual programming. [ABSTRACT FROM AUTHOR]

In order to select the optimal intervals for CBM development, explore the separate layer hydraulic fracturing and multi layered production technology, and promote the exploration and development of CBM in western Guizhou, the hydraulic fracturing and production results of well YMC-1 and the nearby wells are analyzed based on the geological and operation data. The principles to select the optimal formation intervals and drainage production program are determined. The study results show that the 5-2#, 7#, 13-1#, and 13-2# coal seams are the favorable intervals for CBM production. The above multiple coal seams of the favorable intervals can be developed together because of the similar formation pressure. According to the drainage production of well YMC-1, the program can be divided into 5 stages – water drainage to decrease pressure, critical desorption, pressure holding while gas production, production increase by releasing casing pressure, downhole pressure control for stable gas production. And the detailed controlling methods for the 5 stages are summarized. The results of this paper can provide reference for the CBM production of multiple and thin coal seams in western Guizhou. [ABSTRACT FROM AUTHOR]

Due to the shortage and high cost of shipping containers, manufacturers that distribute products for worldwide customers must optimize their delivery. Commonly, they complete their delivery schedule first before creating the production schedule. This article tries to address the scheduling problem arising in the process of creating the production schedule to meet the delivery schedule. The complexity of the situation is increased since there is concern about producing as few product types as possible in a single period and having a balance of production load over multiple periods. A mathematical programming model for addressing this production scheduling problem is proposed in the form of integer programming. This model can be solved using LINGO, a commercial mathematical programming software. Microsoft Excel® spreadsheets are used to store both the data input and the output of the mathematical programming model. The advantages of using Excel are its easy-to-read format and familiarity with most users in various companies. Computational experiments in several cases show that the proposed method is effective to create the production and delivery schedule in various problem settings as expected.

The article describes the SAPFORD-based methodology for reconciling and restructuring the schedules of workshops and sections in the event of failures in the work of production and supply services. An efficient method is proposed for constructing a unified production schedule for a plant, optimized by the criterion of minimizing costs associated with servicing work in progress and penalties for delays in order fulfillment. The task of planning custom-made production is decomposed into subtasks of distributing work to workplaces with specified parameters within acceptable time frames. For each work, the target function of the dependence of the increase in the production price on the amount of delay or premature execution of the work is set and the time of its execution is calculated for which the delivery date of the product is not violated and the "idling" time of the part before the operation starts is minimal. The criteria for subtasks are coordinated by the method of mutual penalties, the essence of which is that the competing jobs in the queues penalize each other with increments of their estimates when letting the competitor take the lead. The first in line is the work with the smallest sum of its own criteria and penalties for delaying competitors. If there are production delays in one shop, the estimates of delayed orders are recalculated and the work in other shops is reordered. The results of the recalculation of the shop operation plans are reflected in the shop nomenclatures of priority works. An example of the solution is given. [ABSTRACT FROM AUTHOR]

Economic lot scheduling problem (ELSP) handles the problem of deciding what order quantities to use when different products/items are produced in the same capacity constrained production facility. It has previously been shown, and it is shown in this article, that it is possible to find a feasible solution fulfilling true feasibility conditions. However, if the utilisation of the production facility is high the production often has to start before the inventory reaches zero to avoid future shortages. Such ‘early starts’ creates an extra inventory holding cost that the traditional approximation for the inventory holding cost does not account for. This article presents an iterative solution procedure that computes the true inventory holding cost and minimises the total costs. Contrary to previous solution procedures, this procedure requires that the production is scheduled in detail. The heuristic solution procedure is illustrated by a numerical example, it is programmed in MATLAB and variants of the problem are presented. [ABSTRACT FROM PUBLISHER]

There are obvious differences in the reservoir-forming mechanisms, flow mechanisms, and production trends between a multilayer superposed CBM system and a single CBM system. This paper performed large-scale physical simulations of CBM production in a multilayer superposed gas-bearing system. According to the experimental results, during commingled production, gas backfilling from a high initial reservoir pressure coal seam into a low reservoir pressure coal seam (LRPCM) occurred, which restrained or even shielded gas production from the low initial reservoir pressure coal seam. Progressive production effectively prevented gas backfilling by optimizing the gas production time of the coal seam, giving the coal seam a more reasonable productivity distribution. The permeability of the two production schedules showed obvious differences in the early stage, which gradually decreased in the middle and late stages. Different values of the coefficient D showed that progressive production provided a better production schedule. Unlabelled Image • Large-scale physical simulations of CBM production in a multilayer superposed gas-bearing system were conducted. • The progressive production schedule for preventing gas backfilling was proposed. • The difference coefficient D for evaluating the different production effects between two production schedules was defined. [ABSTRACT FROM AUTHOR]

Goal: This work aims to compare performance indicators of the pulled, pushed and hybrid production schedule, with those of a specific production environment of the printing industry, using computational simulation. Design / Methodology / Approach: Through a case study, it was possible to create a conceptual model, from which a computational model that was verified and validated as representative of the real productive system was developed. There are generated fictional models of the production environments to compare cycle time, work in process and attendance to the demand, varying the quantity of orders confirmed by the final clients. Results: The CONWIP (Constant Work in Process) system presented very high cycle times and failure to meeting the demand, although it was kept in the format of the work in process. The real system and the pushed system obtained the worst performances regarding the work in process, besides presenting failures to meeting the demand and very high cycle times. The pulled system obtained the best performance to meet the demand, and cycle times adequate to the production requirement and moderate work in process. Limitations of the investigation: The application of the methodology was limited to the study of a single productive system of a print industry and cannot be extended to the entire sector. Practical implications: This work presents a practical application of computer simulation tools applied to Production Planning and Controls which may be replicated by other organizations or educational institutions for system performance analysis in different scenarios. Originality / Value: The original contribution of this work is the application of computational simulation for a production system in a print industry without interference in a real system. [ABSTRACT FROM AUTHOR]

Introduction: Job Shop (JS) production systems are characterized by different route process of the Jobs to be processed. A generalization of this type of systems is the Flexible Job Shop (FJS), in which there is more than one machine per station to perform some of the operations. Objective: The objective of this project was to propose a mixed integer linear programming model to program FJS systems in order to minimize the number of tardy jobs. Methodology: The model was developed using an approach based on sequence-position variables. This approach uses binary variables to decide whether a given operation is assigned to a position in the processing sequence of the assigned machine. To validate the performance of the model data from a small company with an FJS type production system, that develops its operations in an environment to order (MTO), was used. For this reason, the most important performance indicators for the company are those associated with the service level. Results: The results show a reasonable performance in terms of the objective pursued. The optimal production schedule was found in less than 3600 seconds in instances of less than 14 production orders. In larger instances, it obtained feasible solutions within the defined time limit. Conclusions: The model allows defining production schedules in systems in which the fulfillment of due dates is of vital importance. The results have allowed the company to improve its performance and reduce the costs associated with non-compliance of customer’s due dates. Future research can be developed to find more efficient solution methods in terms of computational times to obtain solutions of larger instances.

Goal: This work aims to compare performance indicators of the pulled, pushed and hybrid production schedule, with those of a specific production environment of the printing industry, using computational simulation. Design / Methodology / Approach: Through a case study, it was possible to create a conceptual model, from which a computational model that was verified and validated as representative of the real productive system was developed. There are generated fictional models of the production environments to compare cycle time, work in process and attendance to the demand, varying the quantity of orders confirmed by the final clients. Results: The CONWIP (Constant Work in Process) system presented very high cycle times and failure to meeting the demand, although it was kept in the format of the work in process. The actual real system and the pushed system obtained the worst performances regarding the work in process, besides presenting failures to meeting the demand and very high cycle times. The pulled system obtained the best performance to meet the demand, and cycle times adequate to the production requirement and moderate work in process. Limitations of the investigation: The application of the methodology was limited to the study of a single productive system of a print industry and cannot be extended to the entire sector. Practical implications: This work presents a practical application of computer simulation tools applied to Production Planning and Controls which may be replicated by other organizations or educational institutions for system performance analysis in different scenarios. Originality / Value: The original contribution of this work is the application of computational simulation for a production system in a print industry without interference in a real system.

This study presents a novel framework to incorporate the uncertainties associated with load fluctuations and components' availability in a day‐ahead joint energy‐reserve payment cost minimisation (PCM). The payments are calculated based on locational marginal prices (LMPs). Considering these uncertainties, appropriate definitions are not available for energy and reserve LMPs (RLMPs) that suit the probabilistic PCM formulation and reflect the market characteristics. A tri‐level optimisation framework is proposed. The optimisation variables in the first‐level optimisation include commitment status. In the second‐level optimisation, the production schedule and allocated reserves are the optimisation variables. The third‐level problem includes different sub‐problems, each of which related to optimisation of units' production in a single scenario. This tri‐level optimisation is managed to be converted to a linear single‐level optimisation and is solved using an off‐the‐shelf branch‐and‐cut solver. The 10‐unit system is first used to show the impacts of varying the degree of uncertainties. The IEEE Reliability Test System is next analysed to validate the proposed formulation for RLMPs. [ABSTRACT FROM AUTHOR]

We consider a day-ahead electricity market that consists of multiple competing renewable firms (e.g., wind generators) and conventional firms (e.g., coal-fired power plants) in a discrete-time setting. The market is run in every period, and all firms submit their price-contingent production schedules in every day-ahead market. Following the clearance of a day-ahead market, in the next period, each (renewable) firm chooses its production quantity (after observing its available supply). If a firm produces less than its cleared day-ahead commitment, the firm pays an undersupply penalty in proportion to its underproduction. We explicitly characterize firms' equilibrium strategies by introducing and analyzing a supply function competition model. The purpose of an undersupply penalty is to improve reliability by motivating each firm to commit to quantities it can produce in the following day. We prove that in equilibrium, imposing or increasing a market-based undersupply penalty rate in a period can result in a strictly larger renewable energy commitment at all prices in the associated day-ahead market, and can lead to lower equilibrium reliability in all periods with probability 1. We also show in an extension that firms with diversified technologies result in lower equilibrium reliability than single-technology firms in all periods with probability 1. The electronic companion is available at https://doi.org/10.1287/mnsc.2017.2961. This paper was accepted by Serguei Netessine, operations management. [ABSTRACT FROM AUTHOR]