Order Acceptance Research Articles

Evaluating order acceptance policies for divergent production systems with co-production

The impacts of using different order acceptance policies in manufacturing sectors are usually well known and documented in the literature. However, for industries facing divergent processes with co-production (i.e. several products produced at the same time from a common raw material), the evaluation, comparison and selection of policies are not trivial tasks. This paper proposes a framework to enable this evaluation. Using a simulation model that integrates a custom-built ERP, we compare and evaluate different order acceptance policies in various market conditions. Experiments are carried out using a case from the forest products industry. Results illustrate how and when different market conditions related to divergent/co-production industries may call for available-to-promise (ATP), capable-to-promise (CTP), and other known strategies. Especially, we show that advanced order acceptance policies like CTP may generate a better income for certain types of market and, conversely to typical manufacturing industries, ATP performs better than other strategies for a specific demand patterns.

Role of psychosocial resources and acceptance of disease in maintaining health with asthma / Rola zasobów psychospołecznych oraz akceptacji choroby w zachowaniu zdrowia w astmie

Abstract Introduction. Asthma is a chronic disease. Risky health behaviours among patients like exposure to allergens or stress, smoking, irregular drug taking, lack of physical activity can exacerbate the condition. Psychosocial resources, like self-efficacy, social support and patient’s acceptance of the condition may prove helpful in coping with the disease. Aim. Investigating health behaviours among asthmatic patients, discussing psychosocial resources and assessing the degree of disease acceptance in order to account for the relationship between the latter two variables. Material and methods. The study group included 100 patients suffering from asthma. A questionnaire designed especially for investigating that group of patients, as well as two standardized tools (the Acceptance of Illness Scale and the General Self-Efficacy Scale) were used. A chi-square test was used for performing a statistical analysis. the level of significance was set at p <0.05. Results. Some 43% of patients assessed their acceptance of the condition as medium, while another 52% assessed their self-efficacy as average. Almost all respondents (91%) received support from their loved ones. Almost all admitted they engaged in some physical activity. Most respondents took drugs irregularly and were exposed to stress; more than a half declared exposure to allergens. The higher their self-efficacy was, the more likely they were to engage in sport activities. Self-efficacy and acceptance of the disease by respondents resulted in a significant decrease in asthma exacerbation incidence. The more support they received, the higher their acceptance of the disease was. Conclusions. The respondents showed both positive and negative health behaviours. Self-efficacy was a significant predictor/ indicator of physical activity only. There was a significant relationship between the support that the patients received and their acceptance of the disease.

Acceptance of the Wiang Order and Its Development from the late Silla to the Early Goryeo Periods

중국 선종의 5가(五家) 7종(七宗) 가운데 최초로 형성된 선종이 위앙종이다. 스승 위산과 제자 앙산의 앞 글자만 따서 위앙종이라고 한다. 위앙종의 선사상은 조사선 사상을 그대로 드러낸 시절인연을 자각하고 일상생활에 철저한 평상무사한 여여불이다. 또한 앙산이 탐원 응진으로 97개의 원상 법을 얻은 뒤에 위산 문하에 들어와 제자들을 제접할 때 원상(圓相)을 활용했다. 우리나라 나말여초에 위앙종의 선풍이 전개되었는데, 대통 · 순지 · 무염에 의해서이다. 위앙종을 최초로 공부한 성주산문 무염의 제자 대통은 법을 받아왔지만, 신라에서 전개하지 않았다. 오관산문 순지는 앙산에게서 법을 얻어 신라로 돌아와 견성성불의 단계와 원리를 17개의 원상으로 체계화했다. 성주산문 무염은 앙산의 설을 근거로 무설토론을 전개했다.BR 중국에서는 북송대에 위앙종이 5대로 법맥이 끊겼는데, 근현대 선사인 허운에 의해 위앙종 선풍이 다시 전개되고, 법맥도 전승되고 있다. 우리나라는 고려 때 지겸이 『종문원상집』을 통해 일원상을 재편집했다. 위앙종의 선풍은 선종사에 발전되거나 전승되지 못했지만, 원상은 당대(唐代) 이후 제자들을 깨우치는 방편으로 활용되기도 하고, 오도송으로 표현되었다.

Acceptance of the Wiang Order and Its Development from the late Silla to the Early Goryeo Periods

중국 선종의 5가(五家) 7종(七宗) 가운데 최초로 형성된 선종이 위앙종이다. 스승 위산과 제자 앙산의 앞 글자만 따서 위앙종이라고 한다. 위앙종의 선사상은 조사선 사상을 그대로 드러낸 시절인연을 자각하고 일상생활에 철저한 평상무사한 여여불이다. 또한 앙산이 탐원 응진으로 97개의 원상 법을 얻은 뒤에 위산 문하에 들어와 제자들을 제접할 때 원상(圓相)을 활용했다. 우리나라 나말여초에 위앙종의 선풍이 전개되었는데, 대통 · 순지 · 무염에 의해서이다. 위앙종을 최초로 공부한 성주산문 무염의 제자 대통은 법을 받아왔지만, 신라에서 전개하지 않았다. 오관산문 순지는 앙산에게서 법을 얻어 신라로 돌아와 견성성불의 단계와 원리를 17개의 원상으로 체계화했다. 성주산문 무염은 앙산의 설을 근거로 무설토론을 전개했다.BR 중국에서는 북송대에 위앙종이 5대로 법맥이 끊겼는데, 근현대 선사인 허운에 의해 위앙종 선풍이 다시 전개되고, 법맥도 전승되고 있다. 우리나라는 고려 때 지겸이 『종문원상집』을 통해 일원상을 재편집했다. 위앙종의 선풍은 선종사에 발전되거나 전승되지 못했지만, 원상은 당대(唐代) 이후 제자들을 깨우치는 방편으로 활용되기도 하고, 오도송으로 표현되었다.

An enhanced ABC algorithm for single machine order acceptance and scheduling with class setups

This paper considers the order acceptance and scheduling problem in a single machine environment where each customer order is characterized by a known processing time, due date, revenue, and class setup time. The objective is to maximize the total revenue. Since the problem is computationally intractable, we first conduct a preliminary study of applying the basic artificial bee colony algorithm to address the problem under study. Specifically, we design appropriate neighborhood operators with respect to the problem. Based on the results of the preliminary study and the problem characteristics, an enhanced artificial bee colony algorithm is developed with a series of modifications. The extensive experimental results indicate that the enhanced artificial bee colony algorithm is both computationally efficient and effective for large sized problem instances.

Negotiation based decision support system for order acceptance

Purpose – The purpose of this paper is to develop a mathematical model of a make-to-order manufacturing company simultaneously negotiating multiple contingent orders that possess conflicting issues in order to achieve order acceptance decisions (OADs). Design/methodology/approach – The paper developed a mathematical model by incorporating probabilistic theory and some theories of negotiation in the OAD problem. The model helps to harness the relationship between the manufacturer and customers of contingent orders on conflicting issues. A numerical example is enumerated to illustrate the working mechanism and sensitivity of the model developed. Findings – In the negotiation-based OAD system, if more than one customer is willing to negotiate on the offer of manufacturer, rather than engaging in one-to-one negotiation, the manufacturer has to negotiate with all the customers simultaneously to maximize the expected contribution and acceptance probability from all the orders. Also, the numerical example illustrates that, sometimes, rejecting an order/orders from the order set gives better results in terms of the expected contribution than continuing negotiations on them. Originality/value – Through continuing research efforts in this domain, certain models and strategies have been developed for negotiation on a one-to-one basis (i.e. negotiation by the manufacture with only one customer at a time). One-to-one negotiation will neither help companies to streamline their production systems nor will it maximize the expected contribution. To the best of the author’s knowledge, so far, this is the first instance of research work in the domain of a joint OAD and negotiation framework that attempts to develop a simultaneous negotiation method for arriving at OADs.

Activities of FCV/Infrastructure Demonstration Program in Japan

The Research Association of Hydrogen Supply/Utilization Technology (HySUT) was established in July 2009 by private companies and organizations with the aim of the commercialization of FCVs and the hydrogen infrastructure. Our objective is to solve the issues of technology, consumer awareness, and social acceptance in order to assist the business establishment through the demonstration. The Japan Hydrogen & Fuel Cell Demonstration Project (JHFC) is a major demonstration program of FCV and hydrogen infrastructure in Japan that began in 2002. We had been operating the technical and social demonstration program called JHFC3 from April 2011 to March 2014 after JHFC1 (2002-2005) and JHFC2 (2006-2010), as a joint research program with New Energy and Industrial Technology Development Organization (NEDO). We operated 13 hydrogen refueling stations (HRSs) in March 2014. 1. Technical and Social Demonstration (JHFC3) We have acquired demonstration data on durability, convenience and practicability of the FCVs and hydrogen infrastructure through the operation of our HRSs serving FCVs and fuel cell buses for the start of commercialization of FCVs. The program was focusing on four technology targets: 1) 70MPa filling technology, 2) Low cost station technology, 3) High frequency operation, 4) Demonstration of total system technology. 2. NEDO’s New Project “Hydrogen utilization technology development” We are now leading five new R&D projects which are essential for the commercialization of HRSs in 2015, such as 1) Fueling, 2) Fueling Hose, 3) Hydrogen Quality Control, 4) Hydrogen Metering, 5) Infrastructure Safety under the NEDO program.

Revenue Management in a Multi-Stage Make-to-Order Production System

In the present paper, we consider the demand management decisions of a manufacturer facing stochastic demand. While in the previous literature, either the order release decisions are fixed upon arrival or a single-stage production environment is assumed, we make online order acceptance and order release decisions in a multi-stage production system. After describing the problem formally as a stochastic dynamic program, we develop a bid-pricebased revenue management approach in which the order acceptance and order release decisions are made based on previously computed bid prices and feasibility according to a linear program describing the multi-stage production system. A numerical study shows the good performance of the approach compared to an ex-post optimal solution in various supply and demand settings as well as the benefits relative to existing models, which work under simplifying assumptions.

A learning and optimizing system for order acceptance and scheduling

Order acceptance and scheduling is an interesting scheduling problem when scheduling and acceptance decisions need to be handled simultaneously. The complexity of the problem causes difficulty for many solution methods. In this paper, we proposed a learning and optimizing system to deal with the order acceptance and scheduling problem with a single-machine and dependent setup times. The aim of this system is to combine the advantages of the hyper-heuristic for learning useful scheduling rules and the meta-heuristic for further refining the solutions from the obtained rules. The experiments show that the proposed system is very effective as compared to other heuristics proposed in the literature. The analyses also show the benefits of scheduling rules obtained by the hyper-heuristic, especially for large-scale problem instances.

A Benders decomposition approach for order acceptance and scheduling problem: a robust optimization approach

In this paper, we consider a simultaneous order acceptance and scheduling problem in a non-identical parallel machines environment. The orders are defined by their due dates, revenues, tardiness penalties, different processing times on the machines, and sequence-dependent setup times. We present an MILP formulation to maximize the profit. Furthermore, we assume that the revenue from an accepted order and the processing times are uncertain and accordingly, develop the robust counterpart of the proposed MILP model. The problem is computationally intractable; therefore, we develop a Benders decomposition approach to solve it. We introduce some valid cuts to accelerate the convergence of the classical Benders algorithm and a heuristic method to obtain the feasible solutions. Through numerical experiments on randomly generated large instances with up to 40 orders and 6 machines, we demonstrate that the proposed Benders decomposition approach outperforms the MILP model.

Improving Chemotherapy Ordering Process.

Chemotherapy is a high-risk medication and is the second most common cause of fatal medication errors. The ordering process can be unsafe and inefficient, putting patients at risk for medication errors. The aim of this project was to decrease the number of chemotherapy order forms with at least one deviation by 50% within 5 months. A multidisciplinary team identified causes for variance in form completion, deficits in knowledge of ordering processes, and acceptance of incomplete orders by the staff. The Plan, Do, Study, Act improvement methodology evaluated the chemotherapy ordering process and found different types of deviations on order forms. Interventions consisted of educating physicians on entering complete information on orders, instituting same-day laboratory work on the day of the physician's visit, standardizing laboratory parameters, performing audits of the order forms manually, and educating nurses on not accepting orders with deviations. All order forms were reviewed, and data were collected on different types of deviations. The following deviations were identified: laboratory test results were not being entered into the order form within 7 days, physicians were not providing their name and pager number, and the days of the chemotherapy cycle were missing from the order forms. Before the intervention, 70.1% of the chemotherapy order forms had at least one deviation. After 5 months of interventions, there was a reduction of 19% in the number of order forms with at least one deviation. Follow-up at 6 months and 1 year showed continuing reductions in the number of chemotherapy orders with at least one deviation. Improvement was a result of collaboration between interdisciplinary departments. The original goal was surpassed as a result of educating physicians and staff and standardizing the ordering process. If the number of deviations in chemotherapy order forms is decreased, oncology patients will receive safe, efficient, and quality care.

The production-distribution problem with order acceptance and package delivery: models and algorithm

The production planning and distribution are among the most important decisions in the supply chain. Classically, in this problem, it is assumed that all orders have to produced and separately delivered; while, in practice, an order may be rejected if the cost that it brings to the supply chain exceeds its revenue. Moreover, orders can be delivered in a batch to reduce the related costs. This paper considers the production planning and distribution problem with order acceptance and package delivery to maximize the profit. At first, a new mathematical model based on mixed integer linear programming is developed. Using commercial optimization software, the model can optimally solve small or even medium sized instances. For large instances, a solution method, based on imperialist competitive algorithms, is also proposed. Using numerical experiments, the proposed model and algorithm are evaluated.

How to Achieve Local Resilience to Flood Risks by Increasing Solidarity: The Example of the “Syndicat Mixte” (Inter-Municipal Cooperation Structure) of the French Territory of Belfort-Montbéliard

This paper illustrates approaches to flooding risk governance in a territory where a high density of population corresponds to a high level of industrial activities and a significant development of transport infrastructures in a transboundary context between France, Germany and Switzerland. In the last few years, some fundamental changes in European official instructions about risks and especially about flooding risks occurred. Substantial public policy challenges remain in order to promote a broad-based resilient territory twinned with local knowledge of sustainable land management and civic participation in local governance. The survey is based on a GIS study and questionnaires with a representative panel of 235 stakeholders from the studied territory. Our statistical results demonstrate that, in spite of a deep-rooted mindset as regards flooding hazards, local population awareness of the territorial vulnerability is not related to important challenges. A hierarchical analysis of the data shows that the awareness of stakeholders is less related to the importance of risks when the territorial level decreases. It also highlights the decline of solidarity among neighbouring communities when the distance from the industrial axis increases. Greatly impacted by flooding risks, industrial activities of the regional basin are paradoxically not really perceived as common challenges. Such a case study illustrates how public policies need to be relevant to the adapted levels. Awareness of common issues is a central target to develop acceptance in order to provide an efficient framework of resilience, including willingness to pay to reduce the risk and solidarity in local development compensations.

Extração de Características de Perfil e de Contexto em Redes Sociais para Recomendação de Recursos Educacionais

This paper presents a proposal that generates individualized educational recommendations, using information spontaneously generated in Social Networks. The main goal is to identify characteristic of user´s profile and context through the use of these systems and his/her social interaction and then make consistent educational recommendations. The proposal evaluation was made from the development of a prototype, a proof of concept and a case study. The evaluation results showed the viability and relevant users´ acceptance in order to extract information about their educational interests, automatically generated from the Facebook social network, enrich these information, find implicit interests and use these information to recommend educational resources. It was also validated the possibility of people recommendation, enabling the establishment of interest network, based on a specific subject, showing good partners to study and research.

Order acceptance and scheduling problems in two-machine flow shops: New mixed integer programming formulations

We present two new mixed integer programming formulations for the order acceptance and scheduling problem in two machine flow shops. Solving this optimization problem is challenging because two types of decisions must be made simultaneously: which orders to be accepted for processing and how to schedule them. To speed up the solution procedure, we present several techniques such as preprocessing and valid inequalities. An extensive computational study, using different instances, demonstrates the efficacy of the new formulations in comparison to some previous ones found in the relevant literature.

Strategic capacity planning for light emitting diode (LED) supply chains across Taiwan and China

This paper describes a mixed-integer programming (MIP) model formulated for strategic capacity planning for light emitting diode (LED) makers of Taiwan, major companies in the global LED market. These firms have complex supply chains across Taiwan and China, and the region’s unique political and economic environment has created not only competitive advantages but also challenges in supply chain management: government regulations require that customer orders be accepted from Taiwan or China according to customer attributes; when conducting manufacturing, Taiwanese firms may need to transfer orders across national borders for reasons such as manufacturing technology (the required technology is available only at certain manufacturing facilities) or more efficient capacity utilization; and there are operations to be performed with specific processing requirements to follow, posing substantial challenges for planners. Motivated by the significance of these firms in the global market, we develop a MIP model with novel features to support their strategic capacity planning, covering demand and manufacturing-related decisions, including order acceptance and transfer, manufacturing starts, capacity expansion, and logistics. We illustrate the model’s performance using modified industry data in a numerical example; we also describe the potential impacts the model may create in industry applications.

Beyond Target Costing: Manufacturing Cost Policy Deployment for New Products

The purpose of this paper is to present a method to quantify the costs of potential losses from production processes for new products to prioritize improvement projects based on the target cost and provide data and information for feasibility studies of continuous improvement projects. The specificity of the manufacturing cost policy deployment for new products is to identify the percentage of cost of future production phases which does not add value from a customer perspective, dynamically throughout the product life cycle. The percentage of non-value added cost is based on loss of each manufacturing process and is determined scientifically based on data and facts. Using the proposed method helps manufacturing companies in the acceptance of certain orders which at first glance are unprofitable. Moreover, the proposed method will help develop scenarios for continuous cost reduction after starting production through continuous improvement of productivity and quality required. The empirical results are based on the study during a year and a half in the automotive company, using action research methodology.

Do-not-resuscitate orders among advanced-stage Chinese lung cancer patients who died in hospital.

Do-not-resuscitate (DNR) orders are an important part of end-of-life care (EOL) for patients with incurable advanced lung cancer. The aim of this study was to investigate the clinical factors related to the acceptance of DNR orders by Chinese patients. This study was a retrospective analysis involving patients with advanced-stage (IIIB or IV) lung cancer who died in hospital at our center from August 2004 through August 2014. The patients' clinical characteristics and DNR forms were reviewed. Of the 348 patients enrolled, 260 (74.7 %) provided DNR orders signed only by surrogates. The signing rate of DNR orders increased annually. The median interval from signing a DNR order to death was 1 day (range, 0-72 days). Patients with poor performance status (PS) (≥2) 1 week prior to death (OR, 3.395; 95 % CI, 1.536-7.502, P = 0.003) and relatively longer overall survival (OS) (>3 months) (OR, 2.464; 95 % CI, 1.566-4.472, P < 0.001) were more likely to sign DNR orders. CPR was performed on 10.3 % (27/260) of patients with DNR orders, and was withheld in 22.7 % (20/88) of patients without DNR orders. The DNR order-signing rate has been increasing annually among terminal patients with lung cancer in China. DNR orders, all of which were signed by surrogates, were more likely to be accepted by patients with slowly deteriorating disease and longer OS. More effort should be taken to help patients and medical professionals establish a sensible understanding of EOL care, including DNR orders, at earlier points during the disease course.

Order acceptance and scheduling on two identical parallel machines

We study the order acceptance and scheduling problem on two identical parallel machines. At the beginning of the planning horizon, a firm receives a set of customer orders, each of which has a revenue value, processing time, due date, and tardiness weight. The firm needs to select orders to accept and schedule the accepted orders on two identical parallel machines so as to maximize the total profit. The problem is intractable, so we develop two heuristics and an exact algorithm based on some optimal properties and the Lagrangian relaxation technique. We evaluate the performance of the proposed solution methods via computational experiments. The computational results show that the heuristics are efficient and effective in approximately solving large-sized instances of the problem, while the exact algorithm can only solve small-sized instances.

Non-permutation flow shop scheduling with order acceptance and weighted tardiness

This paper studies the non-permutation solution for the problem of flow shop scheduling with order acceptance and weighted tardiness (FSS-OAWT). We formulate the problem as a linear mixed integer programming (LMIP) model that can be optimally solved by AMPL/CPLEX for small-sized problems. In addition, a non-linear integer programming (NIP) model is presented to design heuristic algorithms. A two-phase genetic algorithm (TP-GA) is developed to solve the problem of medium and large sizes based on the NIP model. The properties of FSS-OAWT are investigated and several theorems for permutation and non-permutation optimum are provided. The performance of the TP-GA is studied through rigorous computational experiments using a large number of numeric instances. The LMIP model is used to demonstrate the differences between permutation and non-permutation solutions to the FSS-OAWT problem. The results show that a considerably large portion of the instances have only an optimal non-permutation schedule (e.g., 43.3% for small-sized), and the proposed TP-GA algorithms are effective in solving the FSS-OAWT problems of various scales (small, medium, and large) with both permutation and non-permutation solutions.