An equitable approach to the payment scheduling problem in project management

This study reports on a new approach to the payment scheduling problem. In this approach, the amount and timing of the payments made by the client and received by the contractor are determined so as to achieve an equitable solution. An equitable solution is defined as one where both the contractor and the client deviate from their respective ideal solutions by an equal percentage. The ideal solutions for the contractor and the client result from having a lump sum payment at the start and end of the project respectively. A double loop genetic algorithm is proposed to solve for an equitable solution. The outer loop represents the client and the inner loop the contractor. The inner loop corresponds to a multi-mode resource constrained project scheduling problem with the objective of maximizing the contractor's net present value for a given payment distribution. When searching for an equitable solution, information flows between the outer and inner loops regarding the payment distribution over the event nodes and the timing of these payments. An example problem is solved and analyzed. A set of 93 problems from the literature are solved and some computational results are reported

Efficient solutions to the cell-formation problem with multiple routings via a double-loop genetic algorithm

We present a genetic approach for finding efficient solutions to the problem of forming manufacturing cells for products having multiple routings. We consider the case where there are two criteria. The method that we propose seeks to generate the efficient set of solutions, that is the set of non-dominated solutions. The manager may then choose a solution knowing the consequences for each of the objectives. We address the computational difficulty of this problem and present a numerical example

Meta-heuristics in cellular manufacturing: A state-of-the-art review

Meta-heuristic approaches are general algorithmic framework, often nature-inspired and designed to solve NP-complete optimization problems in cellular manufacturing systems and has been a growing research area for the past two decades. This paper discusses various meta-heuristic techniques such as evolutionary approach, Ant colony optimization, simulated annealing, Tabu search and other recent approaches, and their applications to the vicinity of group technology/cell formation (GT/CF) problem in cellular manufacturing. The nobility of this paper is to incorporate various prevailing issues, open problems of meta-heuristic approaches, its usage, comparison, hybridization and its scope of future research in the aforesaid area

Grup teknolojisinde parça ailesi ve imalat hücresi oluşturma: bir örnek inceleme

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Grup teknolojisi felsefesinin özünde, tekrarlanan işlerdeki benzerlikleri bir araya getirerek üretim çevriminin hemen hemen her şamasında verimliliği maksimize etme amacı yer alır. Grup teknolojisinin imalat alanındaki uygulaması olarak tanımlanan hücresel imalat ise, benzer imalat özelliklerine göre parçaların parça aileleri, bu aileleri işleyecek makinelerin de makine grupları halinde gruplandırılmasıdır. Hücresel imalatın imalat ortamlarına sağladığı en önemli katkı, büyük, karmaşık ve kontrolü zor olan imalat sistemlerini, daha küçük ve kontrolü kolay alt sistemlere ayrıştırmasıdır. Bu çalışmanın araştırma problemi, mevcut imalat sistemlerini grup teknolojisi ve hücresel imalat ile tanıştırmak isteyen firmaların bu değişimden ne tür faydalar sağlayacaklarını ve bu değişimin kendilerine yükleyeceği yükümlülükleri ortaya koymak olarak ifade edilebilir. Bu bağlamda bu çalışmanın amaçları şu şekilde sıralanabilir: a) İmalat sistemlerinde mevcut esneklik ve verimlilik problemleri, nedenleri ve bu problemlerin çözümü için geliştirilen yöntem ve yaklaşımlar nelerdir? Bu yöntem ve yaklaşımlar problemin çözümü için ne gibi katkılar sağlamaktadır? b) Hücresel imalata geçişin ilk ve en önemli aşaması olan imalat hücreleri oluşturmanın, fabrikanın mevcut yerleşim planında meydana getireceği değişimler ve bu değişimlerin firmaya verimlilik ve esneklik bakımından sağlayacağı katkılar nelerdir? Bu sorulara yanıt ararken yapılan literatür incelemesine ek olarak, literatürden temin edilen, geleneksel bir üretim sistemi kullanan bir dişli pompa fabrikası örnek inceleme olarak seçilmiş ve fabrikaya ait yerleşim planı hücresel imalata göre yeniden düzenlenmiştir. Örnek incelemeye ait yeni yerleşim planında yer alan imalat hücrelerinin oluşturulmasında kümelendirme yöntemi olarak Derece Sırası Kümelendirme Yöntemi kullanılmış ve yönteme ait algoritma fabrikada mevcut makineler ve işlem gören parçalar üzerinde Excel paket programı desteğiyle uygulanmıştır. Bu çerçevede yapılan çalışma sonucunda, parçaların işlem gereksinimlerine göre oluşturulan imalat hücrelerinin, atölye tipi bir üretim sistemi kullanan bir fabrikada mevcut karmaşık iş akışı, yüksek seviyede proses içi stok, uzun üretim süreleri, düşük makine kullanım ve üretim oranları ve kalite seviyeleri, yüksek üretim maliyetleri vb. olumsuzlukların üstesinden gelerek fabrikaya esneklik ve verimlilik kazandıracak koşulları tesis edebileceği bulguları elde edilmiştir. Bu bakımdan yapılan çalışmanın, rekabet stratejilerini zaman ve maliyet bazlı yapan işletmeler için örnek teşkil edebileceği söylenebilir.In the essence of group technology philosphy, aim of maximizing the productivity takes part nearly in every phase of production process by gathering the similarities of operations that are repeated. Cellular manufacturing, which is described as an application of GT in manufacturing is, gouping parts as part families according to similar manufacturing features and grouping machines as machine groups which operate these part families. The primary contribution of cellular manufacturing is, decomposing the manufacturing systems which are large, complex and difficult to control to subsystems that are smaller and easier to control. The research problem of this study considers what sort of benefits and responsibilities the firms which want to introduce their existing manufacturing systems to group technology and cellular manufacturing, will get from the change. In this respect the objectives of this study can be arranged as: a) What are the flexibility and productivity problems and their reasons that exist in the manufacturing systems and which methods and approaches were developed to solve these problems? What sort of contributions do these methods and approaches provide fort he solution of the problem? b) What kind of changes will forming manufacturing cells, that is the first and the most important phase of transition to cellular manufacturing, produce on existing layout of the factory? And what are the contributions of these changes to the firm from the point of view of productivity and flexibility? In order to answers these questions, in additon to a literature research a gear pump factory that used a traditional manufacturing system was chosen as an example study from the literature and layout of the factory was rearranged according to cellular manufacturing. As a clustering method, Rank Order Clustering method was used to form manufacturing cells which were located in the new layout of example study; and algorithm of the method was applied on existing machines and parts that were operated in the factory with support of Excel package program. Within this framework, findings have been gotten at the end of the study show that, manufacturing cells which were formed according to operation requirements of the parts will be able to overcome negativenesses of the workshop type manufacturing system like complex work-flow, high level work-in-process inventory, long throughout time, low machine utilization, production rate and quality, high production costs etc. and will be able to found conditions that provide flexibility and productivity to the factory. In this respect, it can be said that the study has been done will be able to constitute as an example for the firms which determine competition strategies based on time and cost

Formação de células em sistemas de manufatura: uma abordagem usando algoritmos genéticos

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Tecnológico. Programa de Pós-Graduação em Engenharia ElétricaEsta dissertação aborda o problema de formação de células de manufatura (PFCM). Peças que possuem características de manufatura e/ou projeto são agrupadas juntas, formando famílias de peças, e as máquinas requeridas para produzir estas peças são agrupadas dentro de células de manufatura. Nossa abordagem considera importantes aspectos da manufatura, tais como rotas alternativas de processamento, seqüência de operações, demanda de produção das peças e carga de trabalho das máquinas. Entretanto, nem todos estes aspectos são considerados juntos. Duas funções objetivos, uma para minimizar a movimentação intercelular e outra para minimizar a variação da carga de trabalho nas células são usadas para formar células de máquinas. Para resolver os modelos, nós propomos uma heurística baseada em um algoritmo genético capaz de obter soluções de boa qualidade. Os resultados obtidos em teste demonstram que a abordagem é eficiente e muito promissora

Genetic programming for manufacturing optimisation.

A considerable number of optimisation techniques have been proposed for the solution of problems associated with the manufacturing process. Evolutionary computation methods, a group of non-deterministic search algorithms that employ the concept of Darwinian strife for survival to guide the search for optimal solutions, have been extensively used for this purpose. Genetic programming is an evolutionary algorithm that evolves variable-length solution representations in the form of computer programs. While genetic programming has produced successful applications in a variety of optimisation fields, genetic programming methodologies for the solution of manufacturing optimisation problems have rarely been reported. The applicability of genetic programming in the field of manufacturing optimisation is investigated in this thesis. Three well-known problems were used for this purpose: the one-machine total tardiness problem, the cell-formation problem and the multiobjective process planning selection problem. The main contribution of this thesis is the introduction of novel genetic programming frameworks for the solution of these problems. In the case of the one-machine total tardiness problem genetic programming employed combinations of dispatching rules for the indirect representation of job schedules. The hybridisation of genetic programming with alternative search algorithms was proposed for the solution of more difficult problem instances. In addition, genetic programming was used for the evolution of new dispatching rules that challenged the efficiency of man-made dispatching rules for the solution of the problem. An integrated genetic programming - hierarchical clustering approach was proposed for the solution of simple and advanced formulations of the cell-formation problem. The proposed framework produced competitive results to alternative methodologies that have been proposed for the solution of the same problem. The evolution of similarity coefficients that can be used in combination with clustering techniques for the solution of cell-formation problems was also investigated. Finally, genetic programming was combined with a number of evolutionary multiobjective techniques for the solution of the multiobjective process planning selection problem. Results on test problems illustrated the ability of the proposed methodology to provide a wealth of potential solutions to the decision-maker