Branch and price solution approach for order acceptance and capacity planning in make -to -order operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. ^ For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver.^ The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. ^ The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.^

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

Methodology to create cost estimation models for engineer-to-order operations

This research addresses the problem of cost estimation for product development in engineer-to-order (ETO) operations. An ETO operation starts the product development process with a product specification and ends with delivery of a rather complicated, highly customized product. ETO operations are practiced in various industries such as engineering tooling, factory plants, industrial boilers, pressure vessels, shipbuilding, bridges and buildings. ETO views each product as a delivery item in an industrial project and needs to make an accurate estimation of its development cost at the bidding and/or planning stage before any design or manufacturing activity starts. ^ Many ETO practitioners rely on an ad hoc approach to cost estimation, with use of past projects as reference, adapting them to the new requirements. This process is often carried out on a case-by-case basis and in a non-procedural fashion, thus limiting its applicability to other industry domains and transferability to other estimators. In addition to being time consuming, this approach usually does not lead to an accurate cost estimate, which varies from 30% to 50%. ^ This research proposes a generic cost modeling methodology for application in ETO operations across various industry domains. Using the proposed methodology, a cost estimator will be able to develop a cost estimation model for use in a chosen ETO industry in a more expeditious, systematic and accurate manner. ^ The development of the proposed methodology was carried out by following the meta-methodology as outlined by Thomann. Deploying the methodology, cost estimation models were created in two industry domains (building construction and the steel milling equipment manufacturing). The models are then applied to real cases; the cost estimates are significantly more accurate than the actual estimates, with mean absolute error rate of 17.3%. ^ This research fills an important need of quick and accurate cost estimation across various ETO industries. It differs from existing approaches to the problem in that a methodology is developed for use to quickly customize a cost estimation model for a chosen application domain. In addition to more accurate estimation, the major contributions are in its transferability to other users and applicability to different ETO operations. ^

The order selection and lot sizing problem in the make-to-order environment

This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

Capacity planning methodology for concurrent engineer -to -order operations

This research focuses on developing a capacity planning methodology for the emerging concurrent engineer-to-order (ETO) operations. The primary focus is placed on the capacity planning at sales stage. This study examines the characteristics of capacity planning in a concurrent ETO operation environment, models the problem analytically, and proposes a practical capacity planning methodology for concurrent ETO operations in the industry. A computer program that mimics a concurrent ETO operation environment was written to validate the proposed methodology and test a set of rules that affect the performance of a concurrent ETO operation. ^ This study takes a systems engineering approach to the problem and employs systems engineering concepts and tools for the modeling and analysis of the problem, as well as for developing a practical solution to this problem. This study depicts a concurrent ETO environment in which capacity is planned. The capacity planning problem is modeled into a mixed integer program and then solved for smaller-sized applications to evaluate its validity and solution complexity. The objective is to select the best set of available jobs to maximize the profit, while having sufficient capacity to meet each due date expectation. ^ The nature of capacity planning for concurrent ETO operations is different from other operation modes. The search for an effective solution to this problem has been an emerging research field. This study characterizes the problem of capacity planning and proposes a solution approach to the problem. This mathematical model relates work requirements to capacity over the planning horizon. The methodology is proposed for solving industry-scale problems. Along with the capacity planning methodology, a set of heuristic rules was evaluated for improving concurrent ETO planning. ^

A quantitative approach to the organizational design problem

The span of control is the most discussed single concept in classical and modern management theory. In specifying conditions for organizational effectiveness, the span of control has generally been regarded as a critical factor. Existing research work has focused mainly on qualitative methods to analyze this concept, for example heuristic rules based on experiences and/or intuition. This research takes a quantitative approach to this problem and formulates it as a binary integer model, which is used as a tool to study the organizational design issue. This model considers a range of requirements affecting management and supervision of a given set of jobs in a company. These decision variables include allocation of jobs to workers, considering complexity and compatibility of each job with respect to workers, and the requirement of management for planning, execution, training, and control activities in a hierarchical organization. The objective of the model is minimal operations cost, which is the sum of supervision costs at each level of the hierarchy, and the costs of workers assigned to jobs. The model is intended for application in the make-to-order industries as a design tool. It could also be applied to make-to-stock companies as an evaluation tool, to assess the optimality of their current organizational structure. Extensive experiments were conducted to validate the model, to study its behavior, and to evaluate the impact of changing parameters with practical problems. This research proposes a meta-heuristic approach to solving large-size problems, based on the concept of greedy algorithms and the Meta-RaPS algorithm. The proposed heuristic was evaluated with two measures of performance: solution quality and computational speed. The quality is assessed by comparing the obtained objective function value to the one achieved by the optimal solution. The computational efficiency is assessed by comparing the computer time used by the proposed heuristic to the time taken by a commercial software system. Test results show the proposed heuristic procedure generates good solutions in a time-efficient manner.

What makes online grocers work? A case study analysis of factors contributing to online grocery store profitability

This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. ^ To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. ^ Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. ^ The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance. ^

What Makes Online Grocers Work? A Case Study Analysis of Factors Contributing to Online Grocery Store Profitability

This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance.

Risks to Hospitality Firms in the International Arena

Much potential for growth in hospitality firms exists in foreign countries, but expansion abroad typicality bears additional risks that could be detrimental to the operations. The authors explore those risks, currency exchange risk, and country risk, and offer practical techniques to access, manage, control, and reduce them. Deriving benefits from global opportunities requires effective management of these areas

Participative Budgeting and Participant Motivation: A Review of the Literature

In their discussion - Participative Budgeting and Participant Motivation: A Review of the Literature - by Frederick J. Demicco, Assistant Professor, School of Hotel, Restaurant and Institutional Management, The Pennsylvania State University and Steven J. Dempsey, Fulton F. Galer, Martin Baker, Graduate Assistants, College of Business at Virginia Polytechnic Institute and State University, the authors initially observe: “In recent years behavioral literature has stressed the importance of participation In goal-setting by those most directly affected by those goals. The common postulate is that greater participation by employees in the various management functions, especially the planning function, will lead to improved motivation, performance, coordination, and functional behavior. The authors analyze this postulate as it relates to the budgeting process and discuss whether or not participative budgeting has a significant positive impact on the motivations of budget participants.” In defining the concept of budgeting, the authors offer: “Budgeting is usually viewed as encompassing the preparation and adoption of a detailed financial operating plan…” In furthering that statement they also furnish that budgeting’s focus is to influence, in a positive way, how managers plan and coordinate the activities of a property in a way that will enhance their own performance. In essence, framing an organization within its described boundaries, and realizing its established goals. The authors will have you know, to control budget is to control operations. What kind of parallels can be drawn between the technical methods and procedures of budgeting, and managerial behavior? “In an effort to answer this question, Ronen and Livingstone have suggested that a fourth objective of budgeting exists, that of motivation,” say the authors with attribution. “The managerial function of motivation is manipulative in nature.” Demicco, Dempsey, Galer, and Baker attempt to quantify motivation as a psychological premise using the expectancy theory, which encompasses empirical support, intuitive appeal, and ease of application to the budgetary process. They also present you with House's Path-Goal model; essentially a mathematics type formula designed to gauge motivation. You really need to see this. The views of Argyris are also explored in particular detail. Although, the Argyris study was primarily aimed at manufacturing firms, and the effects on line-supervisors of the manufacturing budgets which were used to control and evaluate their performance, its application is relevant to the hospitality industry. As the title suggests, other notables in the field of behavioral motivation theory, and participation are also referenced. “Behavioral theory has been moving away from models of purported general applicability toward contingency models that are suited for particular situations,” say the authors in closing. “It is conceivable that some time in the future, contingency models will make possible the tailoring of budget strategies to individual budget holder personalities.”

Sales Promotion in Hotels:A British Perspective

In their article - Sales Promotion In Hotels: A British Perspective - by Francis Buttle, Lecturer, Department of Hotel, Restaurant, and Travel Administration, University of Massachusetts and Ini Akpabio, Property Manager, Trusthouse Forte, Britain, Buttle and Akpabio initially state: “Sales promotion in hotels is in its infancy. Other industries, particularly consumer goods manufacturing, have long recognized the contribution that sales promotion can make to the cost-effective achievement of marketing objectives. Sales promotion activities in hotels have remained largely uncharted. The authors define, identify and classify these hotel sales promotion activities to understand their function and form, and to highlight any scope for improvement.” The authors begin their discussion by attempting to define what the phrase sales promotion [SP] actually means. “The Institute of Sales Promotion regards sales promotions as “adding value, usually of a temporary nature, to a product or service in order to persuade the end user to purchase that particular brand as opposed to a competitive brand,” the authors offer. Williams, however, describes sales promotions more broadly as “short term tactical marketing tools which are used to achieve specific marketing objectives during a defined time period,” Buttle and Akpabio present with attribution. “The most significant difference between these two viewpoints is that Williams does not limit his definition to activities which are targeted at the consumer,” is their educated view. A lot of the discussion is centered on the differences in the collective marketing-promotional mix. “…it is not always easy to definitively categorize promotional activity,” Buttle and Akpabio say. “For example, in personal selling, a sales promotion such as a special bonus offer may be used to close the sale; an advertisement may be sales promotional in character in that it offers discounts.” Are promotion and marketing distinguishable as two separate entities? “…not only may there be conceptual confusion between components of the promotional mix, but there is sometimes a blurring of the boundaries between the elements of the marketing mix,” the authors suggest. “There are several reasons why SP is particularly suitable for use in hotels: seasonality, increasing competitiveness, asset characteristics, cost characteristics, increased use of channel intermediaries, new product launches, and deal proneness.” Buttle and Akpabio offer their insight on each of these segments. The authors also want you to know that SP customer applications are not the only game in town, SP trade applications are just as essential. Bonuses, enhanced commission rates, and vouchers are but a few examples of trade SP. The research for the article was compiled from several sources including, mail surveys, telephone surveys, personal interviews, trade magazines and newspapers; essentially in the U.K.

Ecological Science and Transformation to the Sustainable City

There is growing urgency to enhance the sustainability of existing and emerging cities. The science of ecology, especially as it interacts with disciplines in the social sciences and urban design, has contributions to make to the sustainable transformation of urban systems. Not all possible urban transformations may lead toward sustainability. Ecological science helps identify components of resilience that can favor transformations that are more sustainable. To summarize the dynamics and choices involved in sustainable transformations, a “metacity” framework is presented, embracing ecological processes in cities as complementary to those involving society, power, and economy.

Variable Speed Limit Strategies to Reduce the Impacts of Traffic Flow Breakdown at Recurrent Freeway Bottlenecks

Variable Speed Limit (VSL) strategies identify and disseminate dynamic speed limits that are determined to be appropriate based on prevailing traffic conditions, road surface conditions, and weather conditions. This dissertation develops and evaluates a shockwave-based VSL system that uses a heuristic switching logic-based controller with specified thresholds of prevailing traffic flow conditions. The system aims to improve operations and mobility at critical bottlenecks. Before traffic breakdown occurrence, the proposed VSL’s goal is to prevent or postpone breakdown by decreasing the inflow and achieving uniform distribution in speed and flow. After breakdown occurrence, the VSL system aims to dampen traffic congestion by reducing the inflow traffic to the congested area and increasing the bottleneck capacity by deactivating the VSL at the head of the congested area. The shockwave-based VSL system pushes the VSL location upstream as the congested area propagates upstream. In addition to testing the system using infrastructure detector-based data, this dissertation investigates the use of Connected Vehicle trajectory data as input to the shockwave-based VSL system performance. Since the field Connected Vehicle data are not available, as part of this research, Vehicle-to-Infrastructure communication is modeled in the microscopic simulation to obtain individual vehicle trajectories. In this system, wavelet transform is used to analyze aggregated individual vehicles’ speed data to determine the locations of congestion. The currently recommended calibration procedures of simulation models are generally based on the capacity, volume and system-performance values and do not specifically examine traffic breakdown characteristics. However, since the proposed VSL strategies are countermeasures to the impacts of breakdown conditions, considering breakdown characteristics in the calibration procedure is important to have a reliable assessment. Several enhancements were proposed in this study to account for the breakdown characteristics at bottleneck locations in the calibration process. In this dissertation, performance of shockwave-based VSL is compared to VSL systems with different fixed VSL message sign locations utilizing the calibrated microscopic model. The results show that shockwave-based VSL outperforms fixed-location VSL systems, and it can considerably decrease the maximum back of queue and duration of breakdown while increasing the average speed during breakdown.

Regional growth, structural change, and natural disaster

Hurricanes, earthquakes, floods, and other serious natural hazards have been attributed with causing changes in regional economic growth, income, employment, and wealth. Natural disasters are said to cause; (1) an acceleration of existing economic trends; (2) an expansion of employment and income, due to recovery operations (the so-called silver lining); and (3) an alteration in the structure of regional economic activity due to changes in "intra" and "inter" regional trading patterns, and technological change.^ Theoretical and stylized disaster simulations (Cochrane 1975; Haas, Cochrane, and Kates 1977; Petak et al. 1982; Ellson et al. 1983, 1984; Boisvert 1992; Brookshire and McKee 1992) point towards a wide scope of possible negative and long lasting impacts upon economic activity and structure. This work examines the consequences of Hurricane Andrew on Dade County's economy. Following the work of Ellson et al. (1984), Guimaraes et al. (1993), and West and Lenze (1993; 1994), a regional econometric forecasting model (DCEFM) using a framework of "with" and "without" the hurricane is constructed and utilized to assess Hurricane Andrew's impact on the structure and level of economic activity in Dade County, Florida.^ The results of the simulation exercises show that the direct economic impact associated with Hurricane Andrew on Dade County is of short duration, and of isolated sectoral impact, with impact generally limited to construction, TCP (transportation, communications, and public utilities), and agricultural sectors. Regional growth, and changes in income and employment reacted directly to, and within the range and direction set by national economic activity. The simulations also lead to the conclusion that areal extent, infrastructure, and sector specific damages or impacts, as opposed to monetary losses, are the primary determinants of a disaster's effects upon employment, income, growth, and economic structure. ^

A follow-up outcome evaluation of independent living services for foster care youth

This study aimed to evaluate the effectiveness of the Independent Living (IL) program targeting foster youths to prepare them for effective adulthood. The study employed a pre-post, two-group comparative research design. The IL group was composed of 49 young adults who participated in the IL or SIL (subsidized IL) program prior to their emancipation from foster care (mean age, 20.6 years). The comparison was made up of 18 young adults who experienced foster care but never participated in the IL or SIL programs (mean age, 20.2 years). Data were collected via a mailed survey that included the Daniel Memorial Independent Living Assessment (DMILA) and an additional questionnaire developed by the researcher. The study also examined: (1) why youth in foster care do not participate in IL programs, (2) how participating youth evaluate IL services and what recommendations they make to improve services, and (3) the internal consistency of the DMILA. Results suggest that the DMILA assessment has mediocre reliability. IL program participation is associated with better educational, employment, income, housing, early parenting-prevention, transportation, anger control, criminal-prevention, and self-evaluation outcomes. However, IL participation is not associated with better social support, perceived parenting competence, substance abuse-prevention, sexual risk-prevention outcomes, increased knowledge in money management skills, job seeking and job maintenance skills, interpersonal skills, or lower depression. Results also suggest that the outreach activities of the IL program may be flawed. IL participants reported the IL program was doing best in educational preparation, criminal involvement prevention, and money management preparation and least well in parenting preparation, housing preparation, employment preparation, and substance abuse prevention. To improve services, youths recommended primarily that IL counselors develop closer relationships with youths, that IL training better address organizational skills, and that monthly subsidy be raised and SIL eligibility requirements softened. The study's political context and limitations are also discussed and implications are derived regarding prevention, intervention, outreach, mentorship, empowerment, cross-systems collaboration, and future research. ^