Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach

Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.Peer Reviewe

Computer modeling of human decision making

Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making

An equitable approach to the payment scheduling problem in project management

This study reports on a new approach to the payment scheduling problem. In this approach, the amount and timing of the payments made by the client and received by the contractor are determined so as to achieve an equitable solution. An equitable solution is defined as one where both the contractor and the client deviate from their respective ideal solutions by an equal percentage. The ideal solutions for the contractor and the client result from having a lump sum payment at the start and end of the project respectively. A double loop genetic algorithm is proposed to solve for an equitable solution. The outer loop represents the client and the inner loop the contractor. The inner loop corresponds to a multi-mode resource constrained project scheduling problem with the objective of maximizing the contractor's net present value for a given payment distribution. When searching for an equitable solution, information flows between the outer and inner loops regarding the payment distribution over the event nodes and the timing of these payments. An example problem is solved and analyzed. A set of 93 problems from the literature are solved and some computational results are reported

The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

QUANTIFYING AND MANAGING RISK IN AGRICULTURE

Risk and Uncertainty,

Schedules, Calendars and Agendas

Time management instruments such as schedules, calendars and agendas are obvious tools to organise individual and collective action. Besides being of great practical significance in the western world and beyond, these tools are remarkable in that they are rarely questioned by those who are governed by them. Yet, they are tools and as such they can be used by management in organisations. This paper will explore: -why these time instruments are much legs visible than the task itself, -to what extent they are knowingly used by management, and -if their effectiveness is somehow limited to certain activities. It is argued that the unobtrusiveness oftime instruments is related to the natural distinction between content and context. Tasks, intellectual or practical, lead the actors to focus on content. Time management instruments appear to belong to context instead. Hence, they are normally taken for granted, framing the problem.Time; management

Economic Incentives to Retire: A Qualitative Choice Approach

This paper addresses two questions:(1) Are older persons' retirement ages significantly affected by the opportunities for income from earnings,private pensions, and Social Security and for leisure at alternative retirement ages?; and (2) How large are the estimated responses? Our approach to modeling the retirement problem is a forward-looking one, in which the explanatory variables include present discounted values of expected lifetime income from earnings, private pensions, and Social Security at all future retirement ages. Such data have been constructed using a unique archive on 390 workers covered by a large union pension plan. A previous paper (Fieldsand Mitchell, 1982) used these data to show that retirement ages are significantly associated with the present discounted value of income at age 60, and with the gain in income from deferring retirement. The current paper develops two different qualitative choice models of the retirement decision. We find: retirement ages do indeed respond significantly to future income and leisure opportunities; an ordered logit model is more suited to the data than is a multinomial logit model; and the estimated responses to changes in future income opportunities differ across model specifications, where the preferred ordered logit model exhibits larger estimated responses.

A needs-based approach to activity generation for travel demand analysis/

Thesis (S.M. in Transportation)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 105-110).This thesis develops a needs-based framework for behavioral enhancement of conventional activity-based travel demand models. Operational activity-based models specify activity generation models based on empirical considerations which are weakly founded in a behavioral theory. This thesis aims to enhance the specification of the activity generation models by developing the conceptual and analytical relationship between individuals' activity choices and need-satisfaction. The theory of needs hypothesizes that individuals conduct activities to satisfy their needs. Each activity that an individual conducts may satisfy one or several of their needs. Conversely, each need may be satisfied by one or several activities. This thesis models an individual's choice of activity dimensions including frequency, sequence, location, mode, time-of-travel, etc. as one that maximizes his/her need-satisfaction. A conceptual model of the relationship between needs and activities is developed based on inventory theory. Every need is associated with a psychological inventory that reflects the level of satisfaction with respect to the need. When an activity that satisfies a need is conducted, the need is satisfied and the corresponding psychological inventory is replenished by a quantity called the activity production. Over time, this inventory gets consumed and the need builds up. The choice of activity dimensions is modeled as a psychological inventory maximizing (i.e. utility-maximizing) problem, subject to time and cost budget constraints. The framework also accounts for satiation in need-satisfaction. An analytical model is formulated, solved and empirically estimated for a single need and the activity that satisfies the need under steady-state conditions. The problem is solved in two stages, for discrete (location) and continuous (duration and frequency) decision variables. The properties of the general solution are studied, and then explored for a translog form of the activity production function. An empirical estimation method that can be applied to single day travel diary data is proposed and validated using Monte-Carlo experiments. The model is empirically estimated using standard travel diary data from the Denver metropolitan area. Estimation results indicate the potential of the needs-based approach to enrich the specification of activity generation models in conventional activity-based model systems. A conceptual framework to extend the single need model is discussed. Extensions to models of multiple needs that capture interactions between different needs are also discussed. The flexible framework can also be extended to model social interactions including intrahousehold activity allocation and joint activity participation by households and social circles. An extension to a dynamic needs-based activity generation model is also discussed, which may be integrated with transportation simulators to predict individuals' activity choices in response to real-time information.by Varun R. Pattabhiraman.S.M.in Transportatio

Women with physical disabilities and the negotiation of leisure constraints

The purpose of this study was to enhance the conceptual understanding of the importance and meaning of constraints to leisure for women with physical disabilities. In-depth qualitative interviews with women with disabilities were used to obtain information about the experience and meanings of leisure. Symbolic interactionism provided the framework for conducting the study. Two major themes emerged relative to constraints to leisure: magnification of leisure constraints for women with physical disabilities, and strategies for negotiating constraints. The data suggested that leisure choices were not necessarily disability-determined, but the context of the disability influenced choices and constraints. Means for negotiating leisure constraints were explicated by examining the lives of women with physical disabilities