Differential evolution to solve the lot size problem.

An Advanced Resource Planning model is presented to support optimal lot size decisions for performance improvement of a production system in terms of either delivery time or setup related costs. Based on a queueing network, a model is developed for a mix of multiple products following their own specific sequence of operations on one or more resources, while taking into account various sources of uncertainty, both in demand as well as in production characteristics. In addition, the model includes the impact of parallel servers and different time schedules in a multi-period planning setting. The corrupting influence of variabilities from rework and breakdown is explicitly modeled. As a major result, the differential evolution algorithm is able to find the optimal lead time as a function of the lot size. In this way, we add a conclusion on the debate on the convexity between lot size and lead time in a complex production environment. We show that differential evolution outperforms a steepest descent method in the search for the global optimal lot size. For problems of realistic size, we propose appropriate control parameters for the differential evolution in order to make its search process more efficient.Production planning; Lot sizing; Queueing networks; Differential evolution;

A content analysis in reverse logistics: a review

The purpose of this paper is to provide a comprehensive review in the various publications on the concept of Reverse Logistics (RL) and the related areas within the period 1998-2012. The content analysis approach has been opted to collect the relevant information from different books, journals, and conferences. A broad review of literature in RL from its emergence until the recent discussions have been analyzed and compared in this research. The findings show that, the theoretical construct in RL has been initiated from the conjunction features in the waste management and logistics activities. This idea had been developed by introducing the new term as RL and its definitions and contents such as the activities; key drivers; barriers to use; material flow, and networks in RL. Furthermore, the findings present the various modelling in different aspects of RL, for instance, the mathematical modelling by applying the existence methods in Multi Attribute Decision-Making Models (MADM). In addition, the environmental concerns and governmental legislatives matters and impacts, which have been highlighted, recently, on RL have been deliberated. Hence, this paper would assist the researchers and practitioners to obtain a broad review of RL in the last decade and, also provide an agenda for the future researches

Optimal design of uptime-guarantee contracts under IGFR valuations and convex costs

An uptime-guarantee contract commits a service provider to maintain the functionality of a customer’s equipment at least for certain fraction of working time during a contracted period. This paper addresses the optimal design of uptime-guarantee contracts for the service provider when the customer’s valuation of a contract with a given guaranteed uptime level has an Increasing Generalized Failure Rate (IGFR) distribution. We first consider the case where the service provider proposes only one contract and characterize the optimal contract in terms of price as well as guaranteed uptime level assuming that the service provider’s cost function is convex. In the second part, the case where the service provider offers a menu of contracts is considered. Given the guaranteed uptime levels of different contracts in the menu, we calculate the corresponding optimal prices. We also give the necessary and sufficient conditions for the existence of optimal contract menus with positive expected profits

The role of the bronchial microvasculature in the airway remodelling in asthma and COPD

In recent years, there has been increased interest in the vascular component of airway remodelling in chronic bronchial inflammation, such as asthma and COPD, and in its role in the progression of disease. In particular, the bronchial mucosa in asthmatics is more vascularised, showing a higher number and dimension of vessels and vascular area. Recently, insight has been obtained regarding the pivotal role of vascular endothelial growth factor (VEGF) in promoting vascular remodelling and angiogenesis. Many studies, conducted on biopsies, induced sputum or BAL, have shown the involvement of VEGF and its receptors in the vascular remodelling processes. Presumably, the vascular component of airway remodelling is a complex multi-step phenomenon involving several mediators. Among the common asthma and COPD medications, only inhaled corticosteroids have demonstrated a real ability to reverse all aspects of vascular remodelling. The aim of this review was to analyze the morphological aspects of the vascular component of airway remodelling and the possible mechanisms involved in asthma and COPD. We also focused on the functional and therapeutic implications of the bronchial microvascular changes in asthma and COPD

Formulating and Solving Sustainable Stochastic Dynamic Facility Layout Problem: A Key to Sustainable Operations

Facility layout design, a NP Hard problem, is associated with the arrangement of facilities in a manufacturing shop floor, which impacts the performance, and cost of system. Efficient design of facility layout is a key to the sustainable operations in a manufacturing shop floor. An efficient layout design not only optimizes the cost and energy due to proficient handling but also increase flexibility and easy accessibility. Traditionally, it is solved using meta-heuristic techniques. But these algorithmic or procedural methodologies do not generate effective and efficient layout design from sustainable point of view, where design should consider multiple criteria such as demand fluctuations, material handling cost, accessibility, maintenance, waste and more. In this paper, to capture the sustainability in the layout design these parameters are considered, and a new Sustainable Stochastic Dynamic Facility Layout Problem (SDFLP) is formulated and solved. SDFLP is optimized for material handling cost and rearrangement cost using various meta-heuristic techniques. The pool of layouts thus generated is then analyzed by Data Envelopment Analysis (DEA) to identify efficient layouts. A novel hierarchical methodology of consensus ranking of layouts is proposed which combines the multiple attributes/criteria. Multi Attribute decision-making (MADM) Techniques such as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Interpretive Ranking Process (IRP) and Analytic hierarchy process (AHP), Borda-Kendall and Integer Linear Programming based rank aggregation techniques are applied. To validate the proposed methodology data sets for facility size N=12 for time period T=5 having Gaussian demand are considered

Differential evolution to solve the lot size problem

An Advanced Resource Planning model is presented to support optimal lot size decisions for performance improvement of a production system in terms of either delivery time or setup related costs. Based on a queueing network, a model is developed for a mix of multiple products following their own specific sequence of operations on one or more resources, while taking into account various sources of uncertainty, both in demand as well as in production characteristics. In addition, the model includes the impact of parallel servers and different time schedules in a multi-period planning setting. The corrupting influence of variabilities from rework and breakdown is explicitly modeled. As a major result, the differential evolution algorithm is able to find the optimal lead time as a function of the lot size. In this way, we add a conclusion on the debate on the convexity between lot size and lead time in a complex production environment. We show that differential evolution outperforms a steepest descent method in the search for the global optimal lot size. For problems of realistic size, we propose appropriate control parameters for the differential evolution in order to make its search process more efficient.status: publishe

Reverse logistics network design: the impact of lead times and stochasticity

status: publishe

A decision support system for the stochastic aggregate planning problem

An advanced decision support system is presented to answer aggregate planning questions regarding the trade-off between demand (product-mix) and supply (capacity) in a multi period stochastic setting. This tool improves the effectiveness and efficiency of sales and operation planning meetings by accounting for both revenues and costs that are relevant at the intermediate planning horizon. We develop a multi product, multi routing model, where a routing consists of a sequence of operations on different resources. Given customer demand in each time period, the model obtains the optimal production quantities in every period for each alternative routing, while explicitly taking into account the stochastic nature of both demand patterns and production lead times. This is the key difference between our approach and traditional aggregate planning models. At the same time, an optimal capacity level for each resource is obtained. We include trade-offs between level and chase strategies by charging costs for inventory, work-in-process, backorders, setups, regular time, overtime, etc. Outsourcing is considered as an alternative source with a stochastic lead time. The methodology builds upon a queueing network to estimate product’s lead time distribution and associated quoted lead time with a service level. More system improvements can be obtained by proper lot sizing. This model is a mixed integer non-linear programming problem. We show that the search process of the differential evolution algorithm is efficient to find stable results within acceptable time limits. A scenario analysis reveals interesting managerial insights.nrpages: 43status: publishe