Modeling reverse logistics process in the agro-industrial sector: The case of the palm oil supply chain

As today’s consumers are more and more concerned with the environmental impacts of products and services they buy, enterprises have been more and more concerned with “green operations”. One of the key aspects of green logistics management is reverse logistics. This paper shows how the potential of managing reverse logistics flows can be implemented in the agro-industrial sector. As an example, the palm oil supply chain is considered. This study is carried out under the focus of the “closed-loop supply chain (CLSC) framework” in which forward and backward product flows are considered simultaneously. A mathematical model is proposed in order to represent the dynamic interaction between flows. The objective function considers energy, cost and economic profits. Different implementation scenarios of recovery processes are proposed and interactions between direct and reverse flows in the chain are evaluated. Results are analyzed using proper statistical tools, showing that the simultaneous analysis of direct and reverse flows positively impact the net economic profits in this complex supply chain of the agro-industrial sector.     

Integrated data envelopment analysis and cooperative game for evaluating energy efficiency of transportation sector: a case of Iran

Annals of Operations Research - Transportation sector with the consumption of 25% of energy play a major role in Iranian economy. This sector produces 27% of total undesirable greenhouse gases in...     

The energy change of weighted graphs

The energy of an (edge)-weighted graph is the sum of the absolute values of the eigenvalues of its (weighted) adjacency matrix. We study how the energy of a weighted graph changes when the weights change. We give some sufficient conditions so that the energy of a weighted graph increases when the positive weight increases. We also characterize some classes of weighted graphs satisfying these sufficient conditions.     

The impact of multi-skilling on personnel scheduling in the service sector: a retail industry case

Using personnel scheduling to reduce overstaffing and understaffing in a service industry across multiple periods is often undermined by lack of flexibility due to the exclusive use of specialized personnel. This study analyses the impacts of assigning multi-skilled personnel to different activities and its potential for improving schedule efficiency. A proposed mixed integer linear programming model determines which employees are trained to work in which activities and their assignments over a one-week planning horizon. The model results show that the lowest total-cost multi-skilled configurations are obtained in scenarios where personnel supply and demand are in equilibrium. Half of employees would continue to be specialized for just one activity while the half slated for multi-skilling would be trained in most cases for just one additional activity, even though training cost is assumed to be minimal. It is also shown that multi-skilling is best applied to employees whose contracts are highly flexible.     

Modelling and simulation of a supply chain in an uncertain environment

This paper describes fuzzy modelling and simulation of a supply chain (SC) in an uncertain environment, as the first step in developing a decision support system. An SC is viewed as a series of facilities that performs the procurement of raw material, its transformation to intermediate and end-products, and distribution and selling of the end-products to customers. All the facilities in the SC are coupled and interrelated in a way that decisions made at one facility affect the performance of others. SC fuzzy models and a simulator cover operational SC control. The objective is to determine the stock levels and order quantities for each inventory in an SC during a finite time horizon to obtain an acceptable delivery performance at a reasonable total cost for the whole SC. Two sources of uncertainty inherent in the external environment in which the SC operates were identified and modelled: customer demand and external supply of raw material. They were interpreted and represented by fuzzy sets. In addition to the fuzzy SC models, a special SC simulator was developed. The SC simulator provides a dynamic view of the SC and assesses the impact of decisions recommended by the SC fuzzy models on SC performance.     

Revenue-based capacity utilisation measures and decomposition: The case of Danish North Sea trawlers

In fisheries, capacity analysis has largely been limited to measuring physical capacity, defined as the maximum amount of output that can be produced per unit of time, given existing plant and equipment and unrestricted availability of variable inputs. An economic measure of capacity can be defined as the maximum revenue attainable for the given fixed inputs, using relevant outputs and output prices. This paper examines these two approaches to capacity by applying data envelopment analysis to physical and economic input/output data for Danish North Sea trawlers. The economic and physical measures are compared and contrasted using correlation analysis. An innovative analysis into the composition of possible revenue increments is also presented and reasons for economic inefficiency of vessels are identified.     

Modelling the benefits of information sharing-based partnerships in a two-level supply chain

This paper presents a study aimed at quantifying the benefits of information sharing-based supply chain partnerships. We derive the optimal inventory policies for the manufacturer and the retailer in a two-level decentralized supply chain under different information sharing scenarios. We show that increasing information sharing among the members in a decentralized supply chain will lead to Pareto improvement in the performance of the entire chain. Specifically, the manufacturer can obtain benefits in terms of reductions in inventory levels and cost savings.     

Robust supply chain network design with multi-products for a company in the food sector

The paper aims to solve a problem faced by a company competing in the snacks market in Turkey. In line with the growth in this market, the company needs to make important decisions over the next few years about the timing and location of a new plant, its initial capacity, the timing and amount of additional capacity to be installed at the new and existing plants, the assignment of demand points to plants and the amount of raw materials to be shipped from suppliers to the plants in each period. The objective is to minimize the total cost of various components. The problem is formulated as a multi-period supply chain network design model with multi products. The resulting mixed-integer linear programming model is solved by the commercial solver CPLEX. This model enables us to carry out all analyses requested by the company in an efficient way. After this deterministic model is solved on the basis of a 9% annual increase in demand, it is extended to a minimax regret model to deal with uncertainty in demand quantities. The results suggest that opening the new plant in the city of İzmir is indeed a robust solution that is unaffected in different scenarios that are based on three distinct demand increase rates. Even though the location of the new plant remains unchanged with respect to scenarios, the optimal robust solution differs from the optimal solution of each scenario in terms of the capacity expansion decisions. After all obtained results had been communicated to the company managers and executives, the new plant construction was started in 2016 very close to the city that the mathematical model had determined. The new plant is expected to start operating in 2018.     

On the relative efficiency of alternative modes of producing a public sector output: The case of the developmentally disabled

This paper examines the relative efficiency of alternative methods of producing care for the developmentally disabled. A linear programming framework is used to construct a production frontier which allows measurement of relative efficiency among institutions in the sample. Tests are performed to detect influential observations in the data which might result from measurement error which could distort the efficiency measures. Different types of institutions are compared in terms of average efficiency. Policy implications of the analysis are discussed in the concluding section.     

Modelling high-tech product life cycles with short-term demand information: a case study

Increasing competition and volatile conditions in high-tech markets result in shortening product life cycles with non-cyclic demand patterns. This study illustrates the use of a demand-characterisation approach that models the underlying shape of product demands in these markets. In the approach, a Bayesian-update procedure combines the demand projections obtained from historical data with the short-term demand information provided from demand leading indicators. The goal of the Bayesian procedure is to improve the accuracy and reduce the variation of historical data-based demand projections. This paper discusses the implementation experience of the proposed approach at a semiconductor-manufacturing company; the key test results are presented using product families introduced over the last few years with a comparison to real-world benchmark demand forecasts.     

Modelling the cost of poor quality in a five-state part manufacturing operation: a case study

The quality history of individual parts from a critical operation can be modeled by a five-state Markov chain involving factory rework operation, customer inspection and field test, parts scrapped, parts defective but used-as-is by concession or re-graded for alternative applications, and defect-free parts satisfying customer requirements. We estimate total failure cost by a five-state Markov chain model and present a case study to demonstrate relationship of the total failure cost to appraisal and prevention costs.     

Modelling of long-term technical change using input-output methods

This paper develops an approach to Input-Output modelling in which the variation with time of I/O coefficients is strongly reduced. It is achieved by a new treatment of joint production and by a new criterion for disaggregation. From the example of four industries it is shown that this approach is very flexible. Long-term extrapolations of I/O coefficients can be made subject to explicit and exogenous constraints which describe the expectations and/or policy options of the modeller.     

Isogeometric structural shape optimization using a fictitious energy regularization

In isogeometric analysis, NURBS basis functions are used as shape functions in an isoparametric finite-element-type discretization. Among other advantageous features, this approach is able to provide exact and smooth representations of a broad class of computational domains with curved boundaries. Therefore, this discretization method seems to be especially convenient for computational shape optimization, where a smooth and CAD-like parametrization of the optimal geometry is desired. Choosing boundary control point coordinates of an isogeometric discretization as design variables, an additional design model can be avoided. However, for a higher number of design variables, typical drawbacks like oscillating boundaries as known from early node-based shape optimization methods appear. To overcome this problem, we propose to use a fictitious energy regularization: the strain energy of a fictitious deformation, which maps the initial to the optimized domain, is employed as a regularizing term in the optimization problem. Moreover, this deformation is used for efficiently moving the dependent nodes within the domain in each step of the optimization process. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Decision conferencing for science prioritisation in the UK public sector: a dual case study

Decision Conferencing, a decision analytic approach, was introduced for science project prioritisation in two organisations of the UK public sector: the National Measurement System Programmes, Unit of the Department of Trade and Industry (now part of the National Measurement Office, an Executive Agency of the Department for Business, Innovation and Skills) and the Science Department of the Environment Agency of England and Wales. Despite some similarities between the organisations, they responded in quite different ways. We describe the organisational contexts in the two organisations, the process by which Decision Conferencing was introduced, and explore possible reasons for the differing experiences.     

A multicriteria decision aid approach for energy planning problems: The case of renewable energy option

In the past, the choice among alternative energy policies at regional level was based only on cost minimization. Lately, it is widely recognized that regional energy planning forms a multi-actor and multicriteria problem. This is particularly true in the case of power generation in regions presenting high rates of increase in electricity demand, together with a significant potential of renewable energy sources, since several and often conflicting points of view must be taken into account. In this paper, the contribution of a Multicriteria Decision Aid method — namely ELECTRE III — addressing in such problems is investigated through the examination of a particular case study in a Greek island. Through the presentation of the procedure followed (identification of actors, selection of criteria, formulation of alternative strategies, application of the specific method and analysis of results and actors' reactions), an effort is made to highlight those aspects that are crucial in reaching a compromise in regional energy planning problems.     

Modelling decision behaviours in pricing game of closed-loop supply chains

This paper experimentally and analytically studies pricing decisions in closed-loop supply chains. Experimental results show considerable deviations from theoretical predictions by traditional pricing models. Moreover, social relationships can affect decision results, and double marginalization is reduced in closed-loop supply chains. For in-depth analysis of experimental results, we further extended the quantal response equilibrium model by incorporating the fairness concerns of both the manufacturer and retailer. The analysis results of the developed model suggest that participants exhibit bounded rationality and fairness concerns when they make decisions. Social relationships can also influence the degree of fairness concerns.     

Modelling in the absence of data: a case study of fleet maintenance in a developing country

Adequate and relevant objective data for modelling maintenance decision problems are often incomplete or not readily accessible. This is particularly true in developing countries. In this paper the experience gained between 1991–95 in conducting a maintenance study of an inter-city express bus fleet in a developing country is presented. The lack of available maintenance records and operating data rendered the study the most data-starved maintenance modelling exercise the authors have met before or since. The study required the use of subjective methods to both define the problem and to estimate parameters, and the application of recently developed concepts in maintenance modelling along with snapshot analysis and delay time modelling. This imposed a structured approach to problem recognition and problem solution. The study contributed both directly and indirectly to a change in work culture and to a reduction in bus breakdown rate. The company was re-visited 5?years later specifically to seek evidence of lasting impact. Some evidence existed and is reported in the paper.     

Modelling of material and structural inhomogeneities in timber structures

The numerical simulation of timber structures by means of FEM has been an object of recent research. Most of the material models developed so far are based on idealized assumptions by disregarding inhomogeneities. Here, models to capture structural inhomogeneities in terms of branches and knots and the resulting deviation in grain course in a three-dimensional FE analysis are presented. Besides, naturally varying material properties referred to as material inhomogeneities have to be considered in the structural analysis. Due to the insufficient experimental data, the uncertainty model fuzziness is applied. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An efficient indicator for structural damage localization using the change of strain energy based on static noisy data

An efficient method is proposed to find multiple damage locations in structural systems. The change of static strain energy (SSE) due to damage is used to establish an indicator for determining the damage location. The SSE is determined using the static analysis information extracted from a finite element modeling. In order to assess the performance of the proposed method for structural damage detection, some benchmark structures having a number of damage scenarios are considered. Numerical results demonstrate that the method can accurately locate the structural damage when considering the measurement noise. The efficiency of the proposed indicator for finding the damage site is also compared with a modal strain energy based index (MSEBI) provided in the literature.