Simultaneous minimization of total tardiness and waiting time variance on a single machine by genetic algorithms

This paper considers a single machine scheduling problem, with the objective of minimizing a linear combination of total tardiness and waiting time variance in which the idle time is not allowed. Minimizing total tardiness is always regarded as one of the most significant performance criteria in practical systems to avoid penalty costs of tardiness, and waiting time variance is an important criterion in establishing quality of service (QoS) in many systems. Each of these criteria is known to be non-deterministic polynomial-time hard (NP-hard); therefore, the linear combination of them is NP-hard too. For this problem, we developed a genetic algorithm (GA) by applying its general structure that further improves the initial population, utilizing some of heuristic algorithms. The GA is shown experimentally to perform well by testing on various instances.     

Competitive performance improvement by operational budget allocation using ANFIS and fuzzy quality function deployment: a case study

A budget is a detailed and comprehensive plan estimated to use a company’s resources over a specific period, and a primary purpose of budget allocation is to drive all activities towards organizational goals. But it seems, often, there is no logical and coherent relationship between overall objectives and action plans. This paper has drawn a consistent relationship between an organization's strategic plans to operational budgeting in a competitive environment. According to the step-by-step model proposed in this article, a strategic plan’s importance considers the main competitors of the market as an external environment factor and a balanced scorecard factors as an internal environment. Both are calculated by an artificial neuro-fuzzy inference systems approach to outshine competing companies. Then, sub-progress must be hierarchically determined in specific plans. In passing, a fuzzy quality function deployment method translates a strategic plan’s weight to detailed task importance (as the smallest component of an operational program) at the mercy of four houses of a quality matrix. An operational budget is allocated to programs for propagating strategic plans in a competitive environment. Finally, a case study in an automobile industry is presented and discussed to illustrate the application of the developed pattern.     

An exploration of green supply chain practices and performances in an automotive industry

During recent years, the natural environment has become a challenging topic that business organizations must consider due to the economic and ecological impacts and increasing awareness of environment protection. Globalization and the increased number of countries entering the World Trade Organization (WTO) have promoted green supply chain management (GSCM) practices in manufacturing organizations. GSCM has emerged as an important organizational philosophy and a proactive approach to reduce environmental risks. Increasing pressures such as stricter regulations, increased community, and consumer pressures, and the developing country’s aim to enter the WTO have caused automotive supply chain managers to consider and to implement GSCM practices to improve both their economic and environmental performances. This paper explores the practices and performances of the GSCM based on the GSCM literature, and it considers the relationship between green supply chain practices (initiatives) and performance outcomes. In this paper, two questionnaires were developed and a survey conducted to assess the importance of GSCM practices and performances in an automotive company in a developing country using a fuzzy multiple criteria decision-making method. The result of this paper presents practical guidance for managers in performing GSCM practices by ranking GSCM practices according to their importance which leads to improving GSCM performances.     

Semantic adaptation of multimedia documents

Multimedia documents have to be played on multiple device types. Hence, usage and platform diversity requires document adaptation according to execution contexts, not generally predictable at design time. In an earlier work, a semantic framework for multimedia document adaptation was proposed. In this framework, a multimedia document is interpreted as a set of potential executions corresponding to the author specification. To each target device corresponds a set of possible executions complying with the device constraints. In this context, adapting requires to select an execution that satisfies the target device constraints and which is as close as possible from the initial composition. This theoretical adaptation framework does not specifically consider the main multimedia document dimensions, i.e., temporal, spatial and hypermedia. In this paper, we propose a concrete application of this framework on standard multimedia documents. For that purpose, we first define an abstract structure that captures the spatio-temporal and hypermedia dimensions of multimedia documents, and we develop an adaptation algorithm which transforms in a minimal way such a structure according to device constraints. Then, we show how this can be used for adapting concrete multimedia documents in SMIL through converting the documents in the abstract structure, using the adaptation algorithm, and converting it back in SMIL. This can be used for other document formats without modifying the adaptation algorithm.     

Heuristic rules for tardiness problem in flow shop with intermediate due dates

In this paper, the tardiness flow shop models with intermediate due date were considered. The flow shop models consist of a set of jobs each having a number of operations, while each operation is performed in a single machine. All the jobs are considered having the same unidirectional precedence order. In the tardiness flow shop models with intermediate due date, which we call the generalized tardiness flow shop models, there exist a due date associated with the completion of each operation, and we want to find a schedule which minimizes the total tardiness of the jobs. This is a more general version of tardiness flow shop in the sense that, by assigning a large value to each of the intermediate due dates, we can obtain the traditional flow shop models. Considering the generalized tardiness flow shop models as the NP-hard problems, a set heuristic sequencing rules for finding the best permutation schedule for such problems is proposed. We conducted an extensive computational experiment using randomly generated test problems for evaluating the efficiency of the proposed rules in obtaining a near-optimal solution. The efficiency of the rules was evaluated, and those rules with better solutions were designated and reported.