Modelling of multi-period multi-product production planning considering production routes

The multi-period multi-product (MPMP) production planning problems, generally, deal with matching production levels of individual products with fluctuated demands over planning horizon. The conventional MPMP optimisation models suffer from insufficient utilisation of available capacity of machines. This fallacy is due to inappropriate formulation of machine capacity and material handling constraints. In this study, a novel mathematical model is proposed to simultaneously optimise production quantities and provide information about managerial decisions such as subcontracting, carrying inventory/backordering, and also hiring/layoff personnel. The problem is then formulated as a mixed integer linear programming (MILP) model by applying appropriate linearisation of non-linear components. The objective is to minimise production costs comprising of production, storage, shortage, subcontracting costs and costs associated with hiring/dismissing labourers. Superiority of the proposed model over existing ones, has been initially evaluated by solving the case presented by Byrne and Bakir [Byrne, M.D. and Bakir, M.A., 1999. Production planning using a hybrid simulation-analytical approach. International Journal of Production Economics, 59 (1), 305–311], and then evaluated by comparing the results obtained from solving both the proposed and the conventional MPMP production planning models using a 100-randomly-generated-test-problem.     

Non-dominated ranked genetic algorithm for a multi-objective mixed-model assembly line sequencing problem

The increasing market demand for product variety forces manufacturers to design mixed-model assembly lines (MMAL) on which a variety of product models similar to product characteristics are assembled. This paper presents a method combining the new ranked based roulette wheel selection algorithm with Pareto-based population ranking algorithm, named non-dominated ranking genetic algorithm (NRGA) to a just-in-time (JIT) sequencing problem when two objectives are considered simultaneously. The two objectives are minimisation the number of setups and variation of production rates. This type of problem is NP-hard. Various operators and parameters of the proposed algorithm are reviewed to calibrate the algorithm by means of the Taguchi method. The solutions obtained via NRGA are compared against solutions obtained via total enumeration (TE) scheme in small problems and also against four other search heuristics in small, medium and large problems. Experimental results show that the proposed algorithm is competitive with these other algorithms in terms of quality and diversity of solutions.     

Graph-neural network approach in cellular manufacturing on the basis of a binary system

In the past several years, many studies have been carried out on cellular manufacturing. Group technology is a manufacturing philosophy in which similar parts are identified and grouped together to take advantage of their similarities in manufacturing and design. The main problem in the development of cellular manufacturing is that of cell formation. In this paper, a graph-neural network approach is given for cell formation problems in group technology. Effort has been made to develop an algorithm that is more reliable than conventional methods. A graph-neural network has the advantages of fast computation and the ability to handle large scale industrial problems without the assumption of any parameter and the least exceptional elements in the presence of bottleneck machines and/or bottleneck parts. Two examples from the literature have been solved to demonstrate the advantages of the algorithm.     

Evaluating strategic issues in supply chain scheduling using game theory

This paper deals with the problem of scheduling and batch delivery of orders in a supply chain (SC) including a supplier, a manufacturer and a final customer. First, the individual decisions of partners in the SC and their behaviours are analysed through mathematical models. Second, the best policy is obtained assuming that the SC is vertically integrated and the partners fully cooperate (this is called SC scheduling in the relevant literature). Since this strategy is usually against a partner, it might not be implemented in practice as the authors have observed this condition in real world. Hence, a fair sharing mechanism based on game theory concepts is also introduced which can motivate the partners to cooperate and adopt the best policy of the SC. The numerical examples show the superiority of integrated decisions over independent actions and also the importance of the sharing mechanism.     

A set partitioning based heuristic procedure for incremental cell formation with routing flexibility

One of the important issues regarding the implementation of cellular manufacturing relates to deciding whether to convert an existing job shop into a cellular manufacturing system comprehensively in a single go, or to convert in stages incrementally wherein the cells are formed one after the other taking the advantage of experiences of implementation. In this paper, a heuristic method based on iterative set partitioning is proposed for incremental cell formation where part operations can be processed on alternative machines. The objective is to minimize cycle time for a given number of workstations. The proposed method is numerically compared with the existing branch and bound technique and another heuristic algorithm based on multistage programming. It is found that the proposed method requires significantly less computational efforts to yield the optimal solution.     

Characterization and microstructure study of low‐density polyethylene by Fourier transform infrared spectroscopy and temperature rising elution fractionation

Infrared spectroscopy is a powerful technique for studying the microstructure and determining the short‐chain branch distribution of polyethylene. In this work, the types and amounts of short‐chain branches in low‐density polyethylene were investigated with Fourier transform infrared spectroscopy, and a new and simple method for the determination of butyl short branches was discovered. The amount of each unsaturated species in low‐density polyethylene was also determined with Fourier transform infrared after the bromination of samples. Furthermore, the resin was fractionated by preparative temperature rising elution fractionation, and the branch distribution and melting endotherm of each fraction were analyzed with attenuated total reflectance/Fourier transform infrared and differential scanning calorimetry. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Predictive simulation-based lighting and shading systems control in buildings

This paper presents a prototypically implemented daylight-responsive lighting and shading systems control in buildings that makes use of real-time sensing and lighting simulation. This system can control the position of window blinds and the status of the luminaires. It operates as follows: (1) at regular time intervals, the system considers a set of candidate control states for the subsequent time step; (2) these alternatives are then virtually enacted via a lighting simulation application that receives input data from a self-updating model of sky (luminance distribution maps obtained via calibrated digital photography), room, and occupancy; (3) the simulation results are compared and ranked according to the preferences (objective function) specified by the occupants and/or facility manager to identify the candidate control state with the most desirable performance.     

Shading and lighting operation in office buildings in Austria: A study of user control behavior

Occupants of buildings typically operate devices such as windows, shades, luminaires, radiators, and fans to bring about desirable indoor environmental conditions. These control actions can have a significant impact on buildings’ performance (energy use, indoor climate). A better understanding of control-oriented user behavior can not only facilitate more accurate predictions of buildings’ performance, but also support the effective operation of buildings’ service systems. This paper describes a study of control-oriented user behavior (as related to systems for lighting and shading) in three office buildings in Austria. The results specifically shed light on the relationships between control actions and environmental conditions inside and outside buildings.     

A DEA approach for comparing solution efficiency in U-line balancing problem using goal programming

Line balancing problem plays an important role in the decision making process to increase efficiency and productivity. Recently, U-shaped layout in many production lines has replaced the traditional straight line layout using just-in-time concept. Here, we propose a model, using multi-objective decision making approach to the U-shaped line balancing problem, to offer enhanced decision maker flexibility, by allowing for conflicting goals. The assembly line operation efficiency is the most significant aim in our study, and this efficiency relates to management of resources and the solution of line balancing problem. First, the U-shaped line balancing problem is solved considering the model's goals. Then, the index function of assembly line balancing is determined and the efficiencies of the optimal solution outputs are evaluated using data envelopment analysis (DEA). Finally, the discrimination weakness and distribution of illogical weight in simple DEA models are resolved using a mixed method.     

A genetic algorithm for the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties

In this paper, we consider the single machine preemptive scheduling problem with linear earliness and quadratic tardiness penalties, with no machine idle time. The problem is strongly NP-hard. We proposed a new mathematical model, with non-linear terms and integer variables. We develop a genetic algorithm for solving the problem in medium and large size. The proposed procedure is compared with optimal solutions for the smaller instance sizes. The genetic procedure is also quite close to the optimum and provided an optimal solution for most of the test problems. Numerical examples show that the proposed algorithm is efficient and effective. Scheduling with early and tardy penalties has received extensive attention from the scheduling community because of its practical significance. Single machine scheduling environments actually occur in several practical applications. Also, the performance of many production systems is often determined by the schedules for a single bottleneck machine. Furthermore, the study of single machine problems frequently provides outcomes that prove functional for more complex scheduling areas.