The reason for developing Advanced PlanningandScheduling (APS) is the problems that arise from different aspects of the production process. Some of these are put forth by (Lee, Jeong and Moon, 2002). One of the problems is customer-specific orders that will be processed in a multi-project environment. This increases the makespan and makes the meeting of the due dates harder. “Capacity is generally scarce because, to be competitive, fixed costs have been reduced by outsourcing in recent Years” (Kolisch, 2000, cited in Lee, Jeong and Moon, 2002). Another need for APS is that ERP systems are not for planning purposes, which makes APS able to complete this gap. APS is found on the principles of hierarchical planning (Hax and Meal, 1973) and make great use of solution approaches that are mathematical programming and meta-heuristics (Stadtler, 2005). In summary, APS seeks to provide managers with information and decisions to manage the company’s Supply Chain, by supporting the material flow and other business areas as procurement, production, transport, distribution and sales (Stadtler, 2005). McKay and Wiers (2003) put forth the scope of APS solutions (cited verbatim for the reader’s understanding):
Energy efficiency is an important issue in wireless sensor networks. A sensor node has a microprocessor and a small amount of memory for signal processing and task scheduling. Dynamic Planning is a method is used in this approach it combines the flexibility of dynamic scheduling with the predictability offered by schedulabilty check. Whenever a node wants to transmit data packet to the other node, the cluster head attempts to guarantee data packets by constructing a plan for its transmission without violating the guarantees of the previously scheduled transmission. ParMyopic scheduling technique is used for transmission. The simulation results shows that the degree of parallelization increases the success ratio for the speedup function used. The resources or file sharing can be done effectively using this Parmyopic scheduling scheme in the wireless sensor network with the deployment of nodes. The query response time is reduced by allowing more than one applications to be executed simultaneously.
Abstract: Due to the instability of markets and the intense competition among companies, detailed scheduling has increasingly become a challenge to management. Companies that focus on the improvement of PPC activities demand tools to meet their needs, such as the finite capacity scheduling tool, also known as Advanced PlanningandScheduling System (APS) to improve delivery times, effective scheduling, and control of the firmed order. This paper aims to identify the needs and difficulties of the detailed production scheduling, the critical factors for implementation, and the benefits that the advanced scheduling systems (APS) can provide. The method used was a survey of companies affiliated to the Federation of Industries of São Paulo (FIESP). The results showed that the detailed production scheduling is a complex activity for most companies, especially for those that adopt make to order strategy (MTO). The majority of companies surveyed use the MRP planning model, but their goals can be more easily achieved with the use of advanced programming systems (APS). Financial costs and lack of training are still limiting factors to implementing those systems.
In spite of fluctuations and uncertainties provoked by the effects of the 2009’s crisis and the reallocation of production sites to emergent countries with cheaper labour force, the control and monitoring domain worldwide has a market value of 190 billion Euros , and within this, the sum of automotive, manufacturing and process industries represents 60% of the total market . Additionally, according to , “Manufacturing is the largest industry market segment for enterprise IT and offers the largest potential market for cloud computing and software as a service”. In this context, planningandscheduling systems assume a critical importance to reach the competitiveness levels of an enterprise placed in the current worldwide market, providing decision support concerning tactical and operational planning, schedulingand real-time optimization methods. The ability to create and adjust long-term plans and short-term schedules according to the production changes, availability of resources and requests from the customers is a key factor for success.
Supply Chain encompasses all those activities needed to design, manufacture and deliver a product or service needs a mechanism or frame work for information sharing. Agent- based manufacturing is a new way of thinking about and applying information. With this idea an attempt is made to provide a multi agent system model for the supply chain management. In the proposed model each agent performs a specific function of the organization and share the information with other agents. There by the most important requirement of effective supply chain i.e information sharing is achieved in the proposed model. In the current work a part of the model related to purchasing activity and the other parts of the model such as functions related to process planningandscheduling activities for the list of items to be manufactured is highlighted.
Operations planningandscheduling (OPS) problems in flexible manufacturing systems (FMSs), are composed of a set of interrelated problems, such as part-type batching, machine grouping, part routing, tool loading, part input sequencing, and resource assignment. The performance of an FMS is highly dependent on the efficient allocation of the limited resources to the tasks, and it is strongly affected by the effective choice of scheduling rules.
Systemic review is one of the most secure and efficient methods since it uses criteria and rules for the composition of your text bank, also known as portfolio. From this, a study of data was carried out in the bibliographic field, which enabled the construction of a dialogue between a theme in the agroindustrial field. Therefore, the main objective of this work was to perform a systemic review research, with the triad: planning, programming and production control, relating to the agroindustrial theme, once, that the theme is much discussed, but little analyzed together. The methodological principles of systemic review were used so that the work could take shape and analysis. In this sense, it is a method of bibliographical research, which seeks to find, in a structured, organized and systematized way, scientific papers of impact, which may serve as a basis for future works. For this research, it was used as the main databases: Academic Google, Scielo, Scopus, CAPES journals and the thesis and dissertations bank of CAPES. As initial results were found 25 works produced in the period between 2012 and 2017. These works also point out in a brief analysis, that the studies that deal with this theme are concentrated in the dimension of the theories that sustain this area, besides constructing reflections on the processes of management and adaptation to contemporary market demands.
Several programs used as tools in forestry planning were developed based on linear programming models (Clutter et al., 1992), such as the Timber RAM (Resource Allocation Model) developed for the USDA Forest Service and used in forest harvest program and the FORPLAN (Forest Planning) developed from Timber RAM, an important forest planning program in the United States. Other programs are currently available, including Implan, Magis, Spectrum, Teams, Stals-3 (Thompson, 1997) and Forplan (Johnson & Stidart, 1987). However, the most outstanding program is SNAP III (Schedulingand Network Analysis Program), developed by Professor John Sessions of Oregon State University, in partnership with the USDA Forest Service (Sessions & Sessions, 1992). SNAP III is a computer program used in harvest and transport planning which considers harvest systems, roads and transport, silvicultural treatments, land and water fauna adjacency restriction, economic analyses etc. The main objectives of this study were to verify, through a case study, the applicability of the SNAP III program as a planning tool for forest harvest and transport
Operational planning within public transit companies has been extensively tackled but still remains a challenging area for operations research models and techniques. This phase of the planning process comprises vehicle scheduling, crew schedulingand rostering problems. In this paper, a new integer mathematical formulation to describe the integrated vehicle-crew-rostering problem is presented. The method proposed to solve this multi-objective problem is a sequential algorithm considered within a preemptive goal programming framework that starts from the solution of an integrated vehicle and crew scheduling problem and ends with the solution of a driver rostering problem. Feasible solutions for the vehicle and crew scheduling problem are obtained by combining a column generation scheme with a branch-and-bound method. These solutions are the input of the rostering problem, which is tackled through a mixed binary linear programming approach. An application to real data of a Portuguese bus company is reported and shows the importance of integrating the three scheduling problems .
micro-periods, in which at most one setup may be performed. Therefore, depending on the models, we are limited to producing at most one or two items per period. Such models are useful for developing short-term production schedules. Lot-sizing andscheduling decisions are taken simultaneously, as here a lot consists in the pro- duction of the same product over one or more consecutive micro-periods. This is the case of discrete lot-sizing andscheduling problem (DLSP), continuous setup lot-sizing problem (CSLP) and proportional setup lot-sizing problem (PLSP). In the DLSP, only one item can be produced in each micro-period and each machine either produces at full capacity or is idle (known as “all-or-nothing” production) – see Fleischmann (1990). The CSLP, presented by Karmarkar and Schrage (1985), is more flexible than the DLSP, relaxing the discrete production policy, as here lot sizes are continuous quantities up to capacity. By relaxing the “all-or-nothing” as- sumption of the DLSP, the CSLP wastes capacity in case a period capacity is not fully used. The PLSP (Drexl and Haase, 1995) is an attempt to avoid this draw- back, by scheduling a second item in a period to use its remaining capacity. As other small-time bucket models, at most one setup may occur within a period. However, contrarily to the DLSP and the CSLP in which setups are performed at the begin- ning of a period, here the setup may take place at any point in time. A criticism to small-bucket models is that for real-world instances they require a prohibitive number of periods, especially if mathematical programming approaches are to be implemented. As opposed to the aforementioned models, the general lot-sizing andscheduling problem (GLSP), first proposed by Fleischmann and Meyr (1997), makes use of a two-level time structure to be more flexible. The planning horizon is di- vided into large buckets (also denoted as macro-periods), with a given length. Each macro-period is partitioned into a fixed number of non-overlapping micro-periods with variable length. The works (Meyr, 2000) and (Meyr, 2002) extend the stan- dard GLSP to cope with sequence-dependent setup times and a parallel machine environment.
Efforts to improve the common ATP model leads to emerge a new type of ATP model, called Advanced ATP which is more compatible with the existing competitive business environment. The exact definition of ATP and Advanced ATP, comparison between them and their applications are completely and comprehensively discussed in a study by Pibernik (2005). Moreover, in this study different classification of Advanced ATPs has been portrayed. One of the most important classifications is to classify Advanced ATP in two groups, batch mode and real-time mode. Each of these has different advantages and applications. In the real-time mode, orders are investigated immediately therefore responsiveness is high. While, in the batch mode, orders which are arrived in a determined interval time would be investigated, simultaneously. Therefore, responsiveness is lower but in this approach a company will not miss more profitable orders. There is no study in the literature which has presented an ATP model for MTF production systems. There is a large portion of industries that work with MTF production system and ATP mechanism can help them improve their production planning. On the other hand, all studies in the literature consider batch mode Advanced ATP (Zhao & O.Ball, 2005; Lin et al., 2010; Cheng & Cheng, 2011) or real-time mode (Volling & Spengler, 2011). Moreover, as the last found gap in ATP literature, most of the reviewed studies have not considered backlog costs. According to these research gaps, in this study we try to design an appropriate ATP model for MTF production systems while trying to combine batch mode and real-time mode and consider holding and tardiness costs. Another immense contribution of this study is to incorporate ATP with job shop scheduling.
Since our desire is to ground the benchmark into reality, we propose to get inspiration from a real assembly cell: the AIP-PRIMECA cell at the University of Valenciennes. From an OR perspective, this system can be viewed as Flexible Job Shop, leading to the formulation of a Flexible Job-Shop Scheduling Problem (FJSP). This section presents then the corresponding generic model and a static instantiation of this model to the AIP-PRIMECA cell. The idea is to ﬁrst formalize a generic FJSP. This formal, highly parameterized model guarantees a certain level of genericity for future studies or for the development of a parameterized linear program. In a second sub- section, an instantiation of this model is proposed according to the static parameters of the AIP-PRIMECA production cell, in other words, all the parameters of the FJSP that will be assumed constant all along this benchmark (e.g., transportation system and its topology, location of machines, standard production times).
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To create a finite-reserve valuation, V , we can choose to utilise one of two methods to arrive at the same un- derlying equation. The first method is the standard in financial mathematics, known as a contingent claims ap- proach. This relies upon being able to constructing a risk-neutral portfolio containing the mine valuation and other suitable traded assets, as originally explained by . The second method is by utilising the Feynman-Kac method probabilistic approach. This method relies upon being able to take expectations, and is fully explained in , in relation to calculating the expected lifetime of an extraction project. In this current paper, we shall explain how the first, contingent claims, approach can be used. We first prescribe four state-space variables. These are the price S per unit of the underlying resource in the ore, the cumulative weight of ore extracted from the mine
appear. However, there are some issues that we need to address. As the adherence to nutritional status evaluation is conditioned by self-reported BMI, this result leads to the conclusion that anthropometric measures obtained by bioelectric impedance in the subgroup (n = 599) should be higher than the remaining group (n = 1313), who had self-reported measures. Consequently, using the real BMI to quantify the overweight/obesity will result in an overestimation of the corresponding prevalence in the studied population. On the other hand, the estimation of prev- alence of overweight/obesity will be underestimated by self-reported measures. For a sub-sam- ple of size n = 395 without missing values in any variable involved, the concordance between these two BMI was obtained, revealing a significant agreement (Kappa = 0.601, p < 0.001). Despite this agreement, 38.2% (13/34) of the participants indirectly self-classified as under- weight were classified by nutritionists as normal BMI. On the other extreme, 30.6% (38/124) of the participants indirectly self-classified as normal BMI were classified as overweight, and 31.0% (27/87) of the respondents self-classified as overweight BMI were obese. Based on the self-reported measures for 1399 individuals, 553 (39.5%) were reported as overweight/obesity with a 95%CI [37.0, 42.1], obtained by Wilson method. In the same way, after excluding four pregnant women, the magnitude of the same event was 338/595 (56.7%) 95%CI [52.7, 60.8], using the real BMI. Taking into account the issues associated with both confidence intervals, we use concepts of an imperfect diagnostic test (self-reported) to correct the first estimate. In fact, it is possible to use the sub-sample with both BMI (n = 395) to estimate the sensitivity (80.6%) and the specificity (90.2%) of the indirect binary self-classification as overweight/obe- sity (yes, no), considering the measures performed by nutritionists as a gold standard. After that, confidence limits for prevalence of overweight/obesity adjusted for sensitivity and speci- ficity are calculated—95%CI [38.4, 45.7]—using Blaker’s, Sterne, Clopper-Pearson and Wilson methods as described by [40, 41].
This paper selects Changsha as a case study and constructs the models of the subway network and the urban spatial network by using planning data. In the network models, the districts of Changsha are regarded as nodes and the connections between each pair of districts are regarded as edges. The method is based on quantitative analysis of the node weights and the edge weights, which are defined in the complex network theory. And the structures of subway and urban space are visualized in the form of networks. Then, through analyzing the discrepancy coefficients of the corresponding nodes and edges, the paper carries out a comparison between the two networks to evaluate the coordination. The results indicate that only 21.4% of districts and 13.2% of district connections have a rational coordination. Finally, the strategies are put forward for optimization, which suggest adjusting subway transit density, regulating land-use intensity andplanning new mass transits for the uncoordinated parts.
Debrix, f., & Barder, a. D. (2009). nothing to fear but fear: Governmentality and the biopolitical production of terror. International Political Sociology, 3(4), 398-413. epstein, D. (1998). afraid/not: Psychoanalytic direc- tions for an insurgent planning history. in L. sandercock (ed.), Making the invisible visible: A multicultural planning history (pp. 209-226). Berkeley: University of California Press. Harvey, D. (2012). Rebel cities. From the right to the city