Operations Research

This paper considers a flexible flow shop scheduling problem, where at least one production stage is made up of unrelated parallel machines.  Moreover, sequence- and machine-dependent setup times are given. The objective is to find a schedule that minimizes a convex sum of makespan and the number of tardy jobs in a static flexible flow shop environment.  For this problem, a 0-1 mixed integer program is formulated.  The problem is however a combinatorial optimization problem which is too difficult to be solved optimally for large problem sizes, and hence heuristics are used to obtain good solutions in a reasonable time.  The proposed constructive heuristics for sequencing the jobs start with the generation of the representatives of the operation time for each operation. Then some dispatching rules and flow shop makespan heuristics are developed. To improve the solutions obtained by the constructive algorithms, fast polynomial heuristic improvement algorithms based on shift moves and pairwise interchanges of jobs are applied.  In addition, metaheuristics are suggested, namely simulated annealing, tabu search and genetic algorithms.  The basic parameters of each metaheuristic are briefly discussed in this paper. The performance of the heuristics is compared relative to each other on a set of test problems with up to 50 jobs and 20 stages and with an optimal solution for small-size problems.  We have found that among the constructive algorithms the insertion based approach is superior to the others, whereas the proposed simulated annealing algorithms are better than tabu search and genetic algorithms among the iterative metaheuristic algorithms.

This study examines both the magnitude of and factors influencing the adoption of 13 horizontal and vertical integration and diversification strategies in a national sample of 797 U S . rural hospitals during the period 1983-1988. Using organization theory, hypotheses were posed relating environmental and market factors, geographic location, and hospital characteristics to the adoption of horizontal and vertical integration and diversification. Results indicate that only one of 13 strategies was adopted by more than 50 percent of all rural hospitals during the study period, and that most of the directional hypotheses were not confirmed using Cox's proportional hazards models. In particular, environmental and market factors were unrelated to the strategies studied. Issues of methodology and theory are discussed; however, during an historically turbulent period, both relatively l o w levels of rural hospital strategic activities and lack of predictive power of the theory suggest caution in relying heavily on a policy for rural hospital survival that is dependent on individual market-oriented strategic behavior.

The growing attention and prominence afforded to analytics presents a genuine challenge for the operational research community. Many in the community have recognised this growth and sought to align themselves with analytics. For instance, the US operational research society INFORMS now offers analytics related conferences, certification and a magazine. However, as shown in this research, the volume of analytics-orientated studies in journals associated with operational research is comparatively low. This paper seeks to address this paradox by seeking to better understand what analytics is, and how operational research is related to it. To do so literature from a range of academic disciplines is analysed, in what is conceived as concurrent histories in the shared tradition of a management paradigm spread over the last 100 years. The findings of this analysis reveal new insights as to how operational research exists within an ecosystem shared with several other disciplines, and how interactions and ripple effects diffuse knowledge and ideas between each. Whilst this ecosystem is developed and evolved through interdisciplinary collaborations, individual disciplines are cast into competition for the attention of the same business users. These findings are further explored by discussing the implication this has for operational research, as well as considering what directions future research may take to maximise the potential value of these relationships.

Selection of the most suitable machine is very crucial in the modern economy to prompt production level as well as revenue generation. In order to endure in the global business scenario, companies must find out the proper way that leads to the successful production environment. Machine selection has become challenging as the number of alternatives and conflicting criteria increase. A decision support system has been developed in this research in machine evaluation process. This framework will act as a guide for decision makers to select the suitable machine via an integrated approach of AHP & TOPSIS. The anticipated methods in this research consist of two steps at its core. In the first step, the criteria of the existing problem are inspected and identified and then the weights of the sector and sub-sector are determined that have come to light by using AHP. In the second step, eligible alternatives are ranked by using TOPSIS. A demonstration of the application of these methodologies in a real life problem is presented.

We employ Cameroonian data on 162 Small and Medium Enterprises (SME) to test fourth competing hypotheses about the impact of Supply Chain Management (SCM) on their performance. The first hypothesis states that there is a relationship between Critical Success Factors (CSFs) for implementation of SCM and SME performance in terms of customer service and satisfaction. In second, there is a significant relationship between CSFs and SME performance in terms of internal business parameters. Third, there is a significant relationship between CSFs and SME performance in terms of financial performance. Fourth, there is a relationship between CSFs and SME performance in terms of innovation and growth. It is evident that SMEs in Cameroon face problems in SCM implementation due to lack of resources and direction. However, successful implementation of SCM can give SMEs an edge over their competitors. Our study identifies some major CSFs for achievement of SCM and studies their impact on performance. Results are analyzed by testing research hypotheses using standard statistical and econometric tools: " devoted resources for supply chain " , " top management commitment " , " development of effective SCM strategy " , " development of reliable suppliers " and " logistics synchronization " emerge as the most pertinent CSFs. Our findings appear to leave little room for explanations of the over/under-performance phenomenon rooted in the trade-off between different forms of managerial capital.

Benefits of customer loyalty scheme and brand loyalty programmes of Accor Hotels: A case study based on Mercure London City Bankside Hotel.

The research on the subject of customer loyalty in the hotel industry and fostering such loyalty through a multi-brand loyalty programme by Accor group of hotel evaluates the concepts relating to behavioural and attitudinal loyalty. It was found that loyalty programs not only reward the customers for repeat purchase behaviour, but also has an important strategic role in collecting the information about the customers. The various viewpoints relating to the implementation of loyalty programs, design of reward schemes and the utilisation of information collected from the customer are discussed. In the case of Accor hotels, there are several brands with differentiated service offerings and the reward scheme is an integrated one. The Accor hotels reward scheme provides points to the customers for staying in the participating hotels/brands such as Sofitel, Pullman, MGallery, Grand Mercure, Novotel, Suite Novotel, Mercure, Adagio, Ibis and Spa.
Through convenience sampling method two managers and four junior managers in the marketing department were interviewed. From the research, and mostly through the interview data it was found that the customers are able to accrue the points for their stay and spend at the hotel, and redeem their loyalty benefits at more than 2500 participating hotels from the lower end Ibis (budget hotel) to the upper end luxury Sofitel and Pullman hotels. The customers are able to exchange these reward points at various points of sale such as at the airports, taxis and related travel services. All the redemptions are targeted at the travelling customer and their needs and hence travelling customers are benefitted. The loyalty programme is also inducing the customer to spend more as the rewards collected can be redeemed against the services of the different hotel properties.
Since there is collaboration between travel and hospitality organisations, Accor hotel is benefitting significantly. It is clear that with the entire organisation the Mercure Hotel is also benefitting from the multi-brand loyalty scheme. The customers at the bottom of the pyramid in the brand structure of Accor group would be moving upwards and there are a considerable number of properties under the lower mid-scale and lowest scale such as the Ibis. The recommendations is to target and capture restaurant customers with the help of direct sales approach from the waiters and customer facing employees in the restaurant to become member in the loyalty programme. The customer-facing employee’s right from the lobby to the restaurant should be provided training to give special service to such repeat customers.

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Ant colony optimization is a technique for optimization that was introduced in the early 1990's. The inspiring source of ant colony optimization is the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems, to continuous optimization problems, and to important problems in telecommunications, such as routing and load balancing. First, we deal with the biological inspiration of ant colony optimization algorithms. We show how this biological inspiration can be transfered into an algorithm for discrete optimization. Then, we outline ant colony optimization in more general terms in the context of discrete optimization, and present some of the nowadays bestperforming ant colony optimization variants. After summarizing some important theoretical results, we demonstrate how ant colony optimization can be applied to continuous optimization problems. Finally, we provide examples of an interesting recent research direction: The hybridization with more classical techniques from artificial intelligence and operations research.

In her close professional relationship to composers, such as Luciano Berio, John Cage, Hans Werner Henze, Igor Stravinsky and Sylvano Bussotti, Cathy Berberian has productively tainted historical preconceptions about the authorial “work” and the role of the singer in the realization of the composer’s creation. Her flamboyant character on the concert stage, where she showcased her more popular work, captured the public’s imagination. The success of this performer–audience rapport was intrinsic to the singer’s performative persona; however Pieter Verstraete argues that through her own composed work ("Stripsody" is the best known), Berberian presented a myriad of personas. She achieved this primarily by deconstructing her own voice as instrument and object, thereby subverting the stability of her relationship to the authorial power of the musical score. Consequently, Berberian’s work invites us to rethink the authorial position of the composer in relation to the singer/performer as well as the enhanced position of the listener whose function it is to imagine such personas in relation to seeing and hearing the performer’s singing body over a number of changing instances.

The Joanna Briggs Institute (JBI) is an international, membership based research and development
organization within the Faculty of Health Sciences at the University of Adelaide. The Institute
specializes in promoting and supporting evidence-based healthcare by providing access to resources
for professionals in nursing, midwifery, medicine, and allied health. With over 80 collaborating centres
and entities, servicing over 90 countries, the Institute is a recognized global leader in evidence-based
healthcare.
The Joanna Briggs Institute (JBI) is an international, membership based research and development
organization within the Faculty of Health Sciences at the University of Adelaide. The Institute
specializes in promoting and supporting evidence-based healthcare by providing access to resources
for professionals in nursing, midwifery, medicine, and allied health. With over 80 collaborating centres
and entities, servicing over 90 countries, the Institute is a recognized global leader in evidence-based
healthcare.

The university canteen is a queuing system with time dependent arrival patterns and limited resources. It has created the problem of students waiting in the queue during the lunch hour. This study purposively selected a Sri Lankan state university canteen composed of two counters and corresponding queues. The data were collected during the lunch hour of five consecutive week days. The sample included 200 students. The queuing system was modeled using the student version of Rockwell ARENA 14.5. The inter arrival times were calculated and inserted to the input analyzer to find the corresponding arrival patterns of students to the university canteen queues. It showed non uniform arrival rates explained by different patterns. The modeled system was run for one hour to find average values for waiting time of the students separately in two queues, number waiting in queues and number of arrivals and service receipts. The simulation showed that 64 students received the service among 64 successive arrivals. The results explained the average waiting times in queue 1 and queue 2 to be 2.35 and 3.03 in minutes respectively. The number waiting at counter 1 and 2 were 1.26 and 1.62 customers. The study further revealed the possibility of reducing waiting times at counter 1 and counter 2 to 0.68 and 0.89 minutes respectively by doubling the resources at both counters. The findings suggested improving the customer service of the system by opening an additional counter during the lunch hour and redesigning the layout considering the financial feasibility.

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This case paper presents the business analysis of Zara, the leading and the profitable brand of Inditex. The case paper's objective is to discuss whether to update the current DOS/IT infrastructure and evaluate the effects of the upgrade. By using the Michael Porter's value chain analysis, we can understand Zara's core business model of vertical integration and assess the areas where IS will add value to the system. The case paper also presents the IS implementation opportunities and evaluating the effectiveness of the implementation. The case paper concludes by providing recommendations for updating the current OS along with its advantages.

Strategy is different from tactics. Tactics is a scheme for a specific manoeuvre whereas strategy is the overall plan for deploying resources to establish a favourable position. According to Thompson & Strickland -"A company's strategy consists of the combination of competitive moves and business approaches that managers employ to please customers and compete successfully and achieve organizational objectives." According to Pearce II & Robinson, Jr. -"Strategy reflects a Company's awareness of law, where and when it should compete; against whom it should compete and for what purpose it should compete."

Although the use of electronic component placement machines has brought reliability and speed to the printed circuit board (PCB) assembly process, to get higher utilization, one needs to solve the resulting complex operations research problems efficiently. In this study, the problem of distributing the assembly workload to two machines deployed on an assembly line with two identical component placement machines to minimize the line idle time is considered. This problem is NP-Complete even in its simplest form. A mathematical model and several heuristics have been proposed to solve this problem efficiently.

Computational grid is a new paradigm in distributed computing which aims to realize a large-scale high performance computing environment over geographically distributed resources. Computational grid enables the sharing, selection, and aggregation of highly heterogeneous resources for solving computational intensive problems in science, engineering and commerce. Numerous efforts have been exerted focusing on various aspects of grid computing including resource specifications, information services, allocation, and security issues. A key issue to meet the computational requirements over grid is resource allocation. Resources in a grid are typically shared and undedicated so that the contention made by various applications results in dynamically fluctuating delays, changing quality of services, and unpredictable behavior, which further complicates the scheduling. On the other hand, architectures and specifications of machines available in a grid are very diverse; therefore, the extent to which a given task can exploit a given architectural feature depends on how well the task's computational requirements match the machine's advanced capabilities. In brief, grid resource management faces to two major problems; one is matching computational needs to appropriate resources, and the other is exploiting resources over highly dynamic environment. In the first part of the thesis, a framework for self-organization for highly dynamic grid is proposed and studied. In the second, third, and forth parts, we have studied methods and algorithms for scheduling over highly heterogeneous grid.

A numerical algorithm for computing necessary conditions for performance specifications is developed for nonlinear uncertain systems. The algorithm is similar in nature and behavior to the power algorithm for the p lower bound, and doesn't rely on a descent method. The algorithm is applied to a practical example.

The Region of Yogyakarta (DIY) is one of the regions in Indonesia. Community growth in Yogyakarta reaches 1.34% in 2017 which can cause various problems such as unemployment community that continues to grow every year. In addition, another serious problem in Yogyakarta is high congestion which is implicated by the increasing number of population in DIY. Those problems have a bad influence on regional cash which is very useful in the development of the area. This study aims to increase regional cash of DIY by considering available employment and traffic congestion. Because the problem is so complex, a system dynamics approach is used to solve it. Based on the simulation results using Powersim 2005, the main cause of unstable regional cash is the high cost of building new roads, the cause of high cost of building new roads is congestion, and the cause of congestion is the high demand for vehicles by residents of the Yogyakarta area. Therefore, it is necessary to reduce the level of demand for vehicles to increase the cash of the DIY area. By reducing the demand for vehicles to 0.00003, which initially 0.00005 has succeeded in making the regional cash stable and increasing continuously. In addition, to increase employment in order to eliminate the population unemployment in Yogyakarta, it can be done by increasing the growth rate of new companies. By increasing the growth rate of the new company to 1.2 which initially 1 has succeeded in making employment increased continuously.

In recent decades, health care costs have dramatically increased, while health care organisations have been under severe pressure to provide improved quality health care for their patients. Several health care administrators have used discreteevent simulation as an effective tool for allocating scarce resources to improve patient flow, while minimising health care delivery costs and increasing patient satisfaction. The rapid growth in simulation software technology has created numerous new application opportunities, including more sophisticated implementations, as well as combining optimisation and simulation for complex integrated facilities. This paper surveys the application of discrete-event simulation modeling to health care clinics and systems of clinics (for example, hospitals, outpatient clinics, emergency departments, and pharmacies). Future directions of research and applications are also discussed.

Albert Stevens, a surgeon and Frank Johnson, a pediatrician, published a paper entitled “A New Eruptive Fever Associated with Stomatitis and Ophthalmia” in the American Journal of Diseases of Children in 1922 [1]. The paper described two young boys who presented with skin eruptions of oval, dark red to purplish spots separated by normal tissue associated with fever, conjunctivitis, inflamed mucous membrane. One boy had total loss of vision. This was the first description of a condition which was
later known as Stevens-Johnson Syndrome (SJS/TEN).

The hypothesis that lean manufacturing audits are an effective way to measure improvements in operational performance was tested using 64 manufacturing sites owned by a FTSE 100 company. Commonly-used lean characteristics were evaluated: policy deployment, standardised work, visual management and housekeeping, quick changeover techniques, total productive maintenance, continuous improvement (kaizen), error proofing, cultural awareness, material control, and levelling (heijunka). Operational performance was assessed employing commonly-used operational performance measures: on-time-delivery, inventory turns, and direct labour utilisation. The findings are that lean manufacturing audits are effective in measuring improvements in operational performance provided that the audit scope and the lean characteristics are aligned up front.

Our global economy is challenged by a surge of events, which provides threat and opportunities alike to the present state of firm and supply chain strategy. Hence it is most import to assess the risk of the existing supply chain partners to have the uninterrupted supply base for the long term growth. The objective of this article is to focus on the risk assessment for the existing supply base of the Tier-1 automotive industry to facilitate the risk mitigation process. The risks of the existing supply base may due to financial, operational and environmental factors. The study will focus only on assessing the financial and op erational risk of the existing supply chain of the identified company based on their past performance. For every type and quantum, a strategy needs to be deployed to overcome the risk.

We study the paper of Xu [Z. Xu, On consistency of the weighted geometric mean complex judgement matrix in AHP, European Journal of Operational Research 126 (2000) 683–687] for the group consistency in analytic hierarchy process of multicriteria decision-making. The purpose of this note is threefold. First, we point out the questionable results in this paper. Second, for three by three comparison matrices, we provide a patchwork for his method. Third, we constructed a counter example to show that in general his method is wrong. Numerical examples are provided to illustrate our findings. If there are four or more alternatives, then we may advise researchers to ignore his results to avoid questionable estimation of group consistency.

After emphasizing the role of consumers in the success and failure of products and services, a methodology is proposed to improve the effectiveness of the creative design and strategic implementation of innovative new products and services. This methodology integrates knowledge in the fields of psychometrics, utility theory and stochastic choice modeling. The methodology consists of a consumer response and a managerial design process. The design process is one of idea generation, evaluation, and refinement while the consumer response is based on consumer measurement, models of the individual choice process, and aggregation of predictions of individual choices. The consumer model interacts with the design process by providing a forecast of consumer acceptance for evaluation and by providing diagnostics on consumer perceptions, preference, choice and segmentation for refinement. The individual response model processes the consumer measures by "reducing" them to an underlying set of perceptual dimensions. "Abstraction" defines homogeneous groups based on preference. "Compaction" describes how the measures of perception combine to produce a scalar goodness measure for each consumer and for each choice alternative. These goodness measures are linked to probability of choice for the new products and services and for competing products and services. In each step theoretical, empirical, and statistical issues are identified. Various existing techniques and new techniques are introduced and described for each phase.

In this paper we propose a dynamic model representing the temporal evolution of the levels of power generation (installed capacity) from two competing sources. These are renewable and conventional (fossil) sources. The percentage penetration rates of renewable and nonrenewable sources are considered as control or decision variables. We introduce an objective functional based on energy demand, production of pollution associated with usage of fossil fuels, and the cost of their systematic substitution by renewable sources. Pontryagin minimum principle is used to determine optimal control policy through minimizing energy generation from fossil fuels while meeting the energy demand as closely as possible through gradual replacement of nonrenewable sources by renewable ones. For different choices of plan periods, optimal generation path along with the corresponding control policies are presented. These results demonstrate that modern control theory can be used effectively to formulate optimal socio-economic policies.

""Origin–destination (O–D) matrix estimation methods based on traffic counts have been largely discussed and investigated. The most used methods are based on Generalised Least Square estimators (GLS) that use as input data a starting O–D matrix and a set of traffic counts. In addition to traffic counts, the analysts could know other general information about travel demand or link flows, based on their experience, or spot data, but few works deal with the matter of including effectively these sources of information.

This paper proposes a Fuzzy-GLS estimation method that allows to improve the estimation performances of classic GLS estimator by including, in addition to traffic counts, uncertain information about starting O–D demand (i.e. outdated estimates, spot data, expert knowledge, etc.). The methods explicitly take into account the relevant level of uncertainty by taking as much advantage as possible from the few vague available data. The method is developed using fuzzy sets theory and fuzzy programming that seems to be a convenient theoretical framework to represent uncertainty in the available data. A solution algorithm for the proposed problem is also presented. The method has been tested by numerical applications and then compared to the classical GLS method under different sets of constraints to the problem.""

Organising shifts, or work rosters, is a problem that affects a large number of businesses where staff are subject to some kind of work rotation or other. Researchers in the fields of Operations Research and Artificial Intelligence have devised several systems in an attempt to optimise the problem. This paper focuses on the problem of medial staff shift rotation at a hospital emergency department, and attempts to establish a method to automate its management by applying genetic algorithms. It also analyses one of the duty rosters that came out of the proposed solution.

We describe an IBM strategic consulting offering involving a methodology and an analytic tool. The methodology, the Risk and Opportunity Assessment, provides a systematic approach for diagnosing problems in the value chain of the enterprise, and for selecting and prioritizing e-business initiatives. Applying this methodology involves the use of an analytic tool, the Value Chain Modeling Tool, that uses management science and operations research techniques, as well as techniques from the domains of finance and supply chain management, to model the endto-end value chain of the enterprise. This approach has been successfully used to improve the financial and operating performance of several enterprises.

The article provides basic information about operations research, introduces the experience of selected applications in terms of the Fire Rescue Service of the Czech Republic presents possible directions for further usage in favor of the development of the security system of the Czech Republic.

A central cycle problem requires a cycle that is reasonably short and keeps the maximum distance from any node not on the cycle to its nearest node on the cycle reasonably low. The objective may be to minimize maximum distance or cycle length. Most classes of central cycle problems are NP-hard. This article investigates insertion heuristics for central cycle problems, drawing on insertion heuristics for p centers and travelling salesman tours. It shows that a modified farthest insertion heuristic has reasonable worst-case bounds. It then compares the performance of two farthest insertion heuristics on a range of problems from TSPLIB. It shows that a simple farthest insertion heuristic performs well in practice.