Efficient Genetic Algorithm for Resource-Constrained Project Scheduling Problem

This paper presents a new genetic algorithm for the resource-constrained project scheduling problem(RCPSP).The algorithm employs a standardized random key(SRK) vector representation with an additional gene that determines whether the serial or parallel schedule generation scheme(SGS) is to be used as the decoding procedure.The iterative forward-backward improvement as the local search procedure is applied upon all generated solutions to schedule the project three times and obtain an SRK vector,which is rese...

Scheduling Multi-Mode Resource-Constrained Projects Using Heuristic Rules Under Uncertainty Environment

Project scheduling is a key objective of many models and is the proposed method for project planning and management.Project scheduling problems depend on precedence relationships and resource constraints,in addition to some other limitations for achieving a subset of goals.Project scheduling problems are dependent on many limitations,including limitations of precedence relationships,resource constraints,and some other limitations for achieving a subset of goals.Deterministic project scheduling models consider all information about the scheduling problem such as activity durations and precedence relationships information resources available and required,which are known and stable during the implementation process.The concept of deterministic project scheduling conflicts with real situations,in which in many cases,some data on the activity’s durations of the project and the degree of availability of resources change or may have different modes and strategies during the process of project implementation for dealing with multi-mode conditions surrounded by projects and their activity durations.Scheduling the multi-mode resource-constrained project problem is an optimization problem whose minimum project duration subject to the availability of resources is of particular interest to us.We use the multi-mode resource allocation and schedulingmodel that takes into account the dynamicity features of all parameters,that is,the scheduling process must be flexible to dynamic environment features.In this paper,we propose five priority heuristic rules for scheduling multi-mode resource-constrained projects under dynamicity features for more realistic situations,in which we apply the proposed heuristic rules(PHR)for scheduling multi-mode resource-constrained projects.Five projects are considered test problems for the PHR.The obtained results rendered by these priority rules for the test problems are compared by the results obtained from 10 well-known heuristics rules rendered for the same test problems.The results in many cases of the proposed priority rules are very promising,where they achieve better scheduling dates in many test case problems and the same results for the others.The proposed model is based on the dynamic features for project topography.

Multi-Mode Resource Constrained Project Scheduling Models for Progress and Equal Time Interval Payments

This study utilizes a time-precedence network technique to construct two models of multi-mode resource constrained project scheduling problem with discounted cash flows （MRCPSPDCF）, individually including the progress payment （PP） and the payment at an equal time interval （ETI）. The objective of each model is to maximize the net present value （NPV） for all cash flows in the project, subject to the related operational constraints. The models are characterized as NP-hard. A heuristic algorithm, coupled with two upper bound solutions, is proposed to efficiently solve the models and evaluate the heuristic algorithm performance which was not performed in past studies. The results show that the performance of proposed models and heuristic algorithm is good.

Urban Food Supply under Constrained Land Resources in Beijing:Potential and Optimization

The recent global food security crisis is garnering increasing attention and calls for innovative solutions to mitigate its negative impacts on people, especially the most economically vulnerable. In urban regions, this issue is aggravated by the fact that, on one hand, rapid urbanization and greater levels and diversity of food consumption associated with the growing affluence of urban inhabitants has led to rising urban food demand, while on the other hand, the rapid loss of farmland due to urban expansion or irrational sprawl and increasing extreme weather events for agricultural producers due to the impact of global climate change is sharply reducing the urban food production and local supply capacity. Therefore how to realize the urban food supply potential and optimize the utilization of the urban farmlands to enhance the local food supply rate and improve urban food security more generally is becoming a key issue. In this paper, we use the case of Beijing to examine the opportunities to enhance the supply of local, affordably priced food under existing land resource constraints, by restructuring farmland utilization. In this paper, we firstly calculate the changes in the food footprint needed by Beijing and its food self-sufficiency rate over the thirty year period from 1981 to 2011. We show that although Beijing’s food footprint has grown from 11 800 to 29 400 km2 over this 30-year period, its food self- sufficiency rate has dropped from 59.3%, 35.8%, 37.3% and 13.1% to about 39.0%, 27.0%, 6.7% and 2.2% for vegetable, fruit, grain and edible oil, respectively. Following this analysis, we calculate Beijing’ s potential food production under different agricultural production allocation scenarios. We conclude that with a proper shift of farmland use, full utilization of temporary idle land, and the development of rooftop farming, Beijing could increase its vegetable self-sufficiency rate to 60% without significantly reducing the production of other types of local food. Given the sensitivity of fresh vegetables to long- distance transport, and the potential to reduce transport-related carbon emissions, this is a worthwhile adjustment that will benefit the city both by meeting the growing need of its residents for fresh food, and by improving the overall regional eco-environment.

A New Algorithm for Resource Constraint Project Scheduling Problem Based on Multi-Agent Systems

The resource constrained project scheduling problem (RCPSP) and a decision-making model based on multi-agent systems (MAS) and general equilibrium marketing are proposed. An algorithm leading to the resource allocation decision involved in RCPSP has also been developed. And this algorithm can be used in the multi-project scheduling field as well.Finally, an illustration is given.

Curve25519 based lightweight end-to-end encryption in resource constrained autonomous 8-bit IoT devices

Robust encryption techniques require heavy computational capability and consume large amount of memory which are unaffordable for resource constrained IoT devices and Cyber-Physical Systems with an inclusion of general-purpose data manipulation tasks.Many encryption techniques have been introduced to address the inability of such devices,lacking in robust security provision at low cost.This article presents an encryption technique,implemented on a resource constrained IoT device(AVR ATmega2560)through utilizing fast execution and less memory consumption properties of curve25519 in a novel and efficient lightweight hash function.The hash function utilizes GMP library for multi-precision arithmetic calculations and pre-calculated curve points to devise a good cipher block using ECDH based key exchange protocols and large random prime number generator function.

Developing a new model for simultaneous scheduling of two grand projects based on game theory and solving the model with Benders decomposition

Grand infrastructure projects,such as dam,power plant,petroleum,and gas industry projects,have several contractors working on them in several independent sub-projects.The concern of reducing the duration of these projects is one of the important issues among various aspects;thus,our aim is to fulfill the requirements by using the game theory approach.In this study,a mixed-integer programming model consisting of game theory and project scheduling is developed to reduce the duration of projects with a minimum increase in costs.In this model,two contractors in successive periods are entered into a step-by-step competition by the employer during dynamic games,considering an exchange in their limited resources.The optimum solution of the game in each stage are selected as the strategy,and the resources during the game are considered to be renewable and limited.The strategy of each contractor can be described as follows:1)share their resources with the other contractor and 2)not share the resources with the other contractor.This model can act dynamically in all circumstances during project implementation.If a player chooses a non-optimum strategy,then this strategy can immediately update itself at the succeeding time period.The proposed model is solved using the exact Benders decomposition method,which is coded in GAMS software.The results suggest the implementation of four step-by-step games between the contractors.Then,the results of our model are compared with those of the conventional models.The projects’duration in our model is reduced by 22.2%.The nominal revenue of both contractors has also reached a significant value of 46078 units compared with the relative value of zero units in the original model.Moreover,we observed in both projects the decreases of 19.5%,20.9%,and 19.7%in the total stagnation of resources of types 1,2,and 3,respectively.