Dynamic resource constrained multi-project scheduling problem with weighted earliness/tardiness costs

In this study, a conceptual framework is given for the dynamic multi-project scheduling problem with weighted earliness/tardiness costs (DRCMPSPWET) and a mathematical programming formulation of the problem is provided. In DRCMPSPWET, a project arrives on top of an existing project portfolio and a due date has to be quoted for the new project while minimizing the costs of schedule changes. The objective function consists of the weighted earliness tardiness costs of the activities of the existing projects in the current baseline schedule plus a term that increases linearly with the anticipated completion time of the new project. An iterated local search based approach is developed for large instances of this problem. In order to analyze the performance and behavior of the proposed method, a new multi-project data set is created by controlling the total number of activities, the due date tightness, the due date range, the number of resource types, and the completion time factor in an instance. A series of computational experiments are carried out to test the performance of the local search approach. Exact solutions are provided for the small instances. The results indicate that the local search heuristic performs well in terms of both solution quality and solution time

On the construction of stable project baseline schedules.

The vast majority of project scheduling efforts assume complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. In reality, however, project activities are subject to considerable uncertainty, which generally leads to numerous schedule disruptions. It is of interest to develop pre-schedules that can absorb disruptions in activity durations without affecting the planning of other activities, such that co-ordination of resources and material procurement for each of the activities can be performed as smoothly as possible. The objective of this paper is to develop and evaluate various approaches for constructing a stable pre-schedule, which is unlikely to undergo major changes when it needs to be repaired as a reaction to minor activity duration disruptions.

Integrating sustainability into production scheduling in hybrid flow-shop environments

Global energy consumption is projected to grow by nearly 50% as of 2018, reaching a peak of 910.7 quadrillion BTU in 2050. The industrial sector accounts for the largest share of the energy consumed, making energy awareness on the shop foors imperative for promoting industrial sustainable development. Considering a growing awareness of the importance of sustainability, production planning and control require the incorporation of time-of-use electricity pricing models into scheduling problems for well-informed energy-saving decisions. Besides, modern manufacturing emphasizes the role of human factors in production processes. This study proposes a new approach for optimizing the hybrid fow-shop scheduling problems (HFSP) considering time-of-use electricity pricing, workers’ fexibility, and sequence-dependent setup time (SDST). Novelties of this study are twofold: to extend a new mathematical formulation and to develop an improved multi-objective optimization algorithm. Extensive numerical experiments are conducted to evaluate the performance of the developed solution method, the adjusted multi-objective genetic algorithm (AMOGA), comparing it with the state-of-the-art, i.e., strength Pareto evolutionary algorithm (SPEA2), and Pareto envelop-based selection algorithm (PESA2). It is shown that AMOGA performs better than the benchmarks considering the mean ideal distance, inverted generational distance, diversifcation, and quality metrics, providing more versatile and better solutions for production and energy efciency

A survey of variants and extensions of the resource-constrained project scheduling problem

The resource-constrained project scheduling problem (RCPSP) consists of activities that must be scheduled subject to precedence and resource constraints such that the makespan is minimized. It has become a well-known standard problem in the context of project scheduling which has attracted numerous researchers who developed both exact and heuristic scheduling procedures. However, it is a rather basic model with assumptions that are too restrictive for many practical applications. Consequently, various extensions of the basic RCPSP have been developed. This paper gives an overview over these extensions. The extensions are classified according to the structure of the RCPSP. We summarize generalizations of the activity concept, of the precedence relations and of the resource constraints. Alternative objectives and approaches for scheduling multiple projects are discussed as well. In addition to popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, the paper also provides a survey of many less known concepts. --project scheduling,modeling,resource constraints,temporal constraints,networks

A Survey of League Championship Algorithm: Prospects and Challenges

The League Championship Algorithm (LCA) is sport-inspired optimization algorithm that was introduced by Ali Husseinzadeh Kashan in the year 2009. It has since drawn enormous interest among the researchers because of its potential efficiency in solving many optimization problems and real-world applications. The LCA has also shown great potentials in solving non-deterministic polynomial time (NP-complete) problems. This survey presents a brief synopsis of the LCA literatures in peer-reviewed journals, conferences and book chapters. These research articles are then categorized according to indexing in the major academic databases (Web of Science, Scopus, IEEE Xplore and the Google Scholar). The analysis was also done to explore the prospects and the challenges of the algorithm and its acceptability among researchers. This systematic categorization can be used as a basis for future studies.Comment: 10 pages, 2 figures, 2 tables, Indian Journal of Science and Technology, 201

Implementation of Critical Path Method and Critical Resource Diagramming Using Arena Simulation Software

A relatively new resource management tool, which considers both time and resource requirements, is Critical Resource Diagramming (CRD). CRD is a simple extension to the CPM technique developed for resource management purposes. It is a graphical tool used mainly for resource scheduling. The purpose of this study is to use the Arena simulation software and CRD to solve problems. This will be accomplished by setting up an example problem in the simulation program, Arena, and the CRD approach will be used as a deterministic and probabilistic problem. The Arena output results for the deterministic parts of the example were compared to the output that was done by hand and the values obtained were exactly the same. Thus, Arena can be used as an effective and accurate management tool for resource scheduling. The probabilistic results of the Arena output show that if the user does not know the exact time of the process, that a distribution can be used to give results. All the user would have to know is the approximate process time, what distribution the process times will follow, and the standard deviation of the distribution. Arena is both easy and a user-friendly simulation software, thus providing a very simple and important tool in the area of project management. In summary, the research reported here has made a significant contribution in enhancing the CPM method and applying the CRD method to a new applicatio