Alkis Vazacopoulos

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In this paper we deal with a variant of the Job Shop Scheduling Problem. We consider the addition of release dates and deadlines to be met by all jobs. The objective is makespan minimization if there are no tardy jobs, and tardiness minimization otherwise. The problem is approached by using a Shifting Bottleneck strategy. The presence of deadlines motivates(More)
We address a scheduling and routing problem faced by a third-party logistics provider in planning its day-of-week delivery schedule and routes for a set of existing and/or prospective customers who need to make shipments to their customers (whom we call “end-customers”). The goal is to minimize the total cost of transportation and inventory while satisfying(More)
Over the past decade there has been a huge improvement in the performance of state-of-the-art MIP codes. Combined with the increased performance of computers over this period the size and complexity of the problems that can be solved has increased enormously. In this paper we take a closer look at some of the hardest problems in the MIPLIB 2003 library(More)
Supply chains continually face the challenge of efficient decision-making in a complex environment coupled with uncertainty. While plenty of forecasting and analytical tools are available in the market to evaluate and enhance Supply Chains’ performance, the current functionalities are not sufficient to address issues related to efficient decision making(More)
Computing with words and perceptions, or CWP for short, is a mode of computing in which the objects of computation are words, propositions and perceptions described in a natural language. Perceptions play a key role in human cognition. Humans-but not machines-have a remarkable capability to perform a wide variety of physical and mental tasks without any(More)
Due to quantity times quality nonlinear terms inherent in the oil-refining industry, performing industrialsized capital investment planning (CIP) in this field is traditionally done using linear (LP) or nonlinear (NLP) models whereby a gamut of scenarios are generated and manually searched to make expand and/or install decisions. Though mixed-integer(More)
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