Decision Making in Manufacturing and Services
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ISSN 1896-8325
e-ISSN: 2300-7087
Issue Date
2013
Volume
Vol. 7
Number
No. 1/2
Description
Journal Volume
Decision Making in Manufacturing and Services
Vol. 7 (2013)
Projects
Pages
Articles
A utility function to solve approximate linear equations for decision making
(2013) Yoneda, Kiyoshi; Celaschi, Walter
Suppose there are a number of decision variables linearly related to a set of outcome variables. There are at least as many outcome variables as the number of decision variables since all decisions are outcomes by themselves. The quality of outcome is evaluated by a utility function. Given desired values for all outcome variables, decision making reduces to »solving« the system of linear equations with respect to the decision variables; the solution being defined as decision variable values such that maximize the utility function. This paper proposes a family of additively separable utility functions which can be defined by setting four intuitive parameters for each outcome variable: the desired value of the outcome, the lower and the upper limits of its admissible interval, and its importance weight. The utility function takes a nonnegative value within the admissible domain and negative outside; permits gradient methods for maximization, is designed to have a small dynamic range for numerical computation. Small examples are presented to illustrate the proposed method.
Application of a Fuzzy Inference System for the optimization of material removal rate and multiple surface roughness characteristics in the machining of GFRP polyester composites
(2013) Singh, Ankita; Datta, Saurov; Mahapatra, Siba Sankar
This paper presents a multi-objective extended optimization methodology applied in the machining of a randomly oriented GFRP rod. Design of Experiment (DOE) has been selected based on a L9 orthogonal array design with varying process control parameters like: spindle speed, feed rate and depth of cut. Multiple surface roughness parameters of the machined FRP product along with the Material Removal Rate (MRR) of the machining process have been optimized simultaneously. The Fuzzy Inference System (FIS) has been proposed for providing feasible means for the meaningful aggregation of multiple objective functions into an equivalent single performance index (MPCI). This Multi-Performance Characteristic Index (MPCI) has been optimized using the Taguchi method. The approach adapted here is capable of overcoming limitations/assumptions of existing optimization methodologies available in the literature.
Modelling set-up times overlapping two periods in the Proportional Lot-Sizing Problem with identical parallel machines
(2013) Kaczmarczyk, Waldemar
This paper presents a new mixed integer programming model for the Proportional Lot-Sizing Problem (PLSP) with identical parallel machines and set-up times overlapping two periods. The proposed model assumes constant period length and explicitly calculates the distribution of set-up operations among periods. The presented results of computational experiments with standard MIP methods prove that the untying set-ups from period borders enables the reduction of the total costs in optimal solutions.
A two-phase algorithm for a Resource Constrained Project Scheduling Problem with Discounted Cash Flows
(2013) Klimek, Marcin; Łebkowski, Piotr
This paper presents a Resource-Constrained Project Scheduling Problem (RCPSP) settled by contractual milestones. The criterion analysed here is the maximisation of aggregate discounted cash flows from the contractor's perspective, known as an RCPSP problem with Discounted Cash Flows (RCPSPDCF). The cash flows analysed here cover the contractor´s cash outflows (negative cash flows), related to the commencement of individual activities, and cash inflows (positive cash flows) after the fulfilment of individual milestones. The authors propose a two-phase algorithm for solving the problem defined. In the first phase, the simulated annealing metaheuristics is used, designed to identify a forward schedule with as high total DCF as possible. In the second phase, the best first-phase schedule is improved by right shifts of activities. To this end, the procedure which iteratively shifts tasks by one unit is applied, with a view to maximising the objective function. Activity shifts take into consideration precedence and resource constraints, and they are performed for a specified resource allocation to activities. This paper also includes an analysis of the problem for a sample project. The results of computational experiments are then analysed. The experiments were run with the use of standard test problems from the Project Scheduling Problem LIBrary (PSPLIB), with additionally defined cash flows and contractual milestones.