Industrial and Systems Engineering

In the doubly-constrained project scheduling problem where nonrenewable resources are constrained both on a period and a project basis, the combinatorial complexity arising from interrelated Precedence, renewable and nonrenewable resource constraints necessitates a solution approach which takes all such considerations into account including the objectives. In this context arl activity is permitted to oPerate in one of its modes, each of which represents the trade off between different choices of resource requirements (types) and operating durations. The proposed heuristic approach to handle this problem is local constraint based analysis (LCBA) where the selection of activities and their respective modes is made locally at every decision point. LCBA imposes precedence relationships on activities which guarantee the feasibility of the current makespan constrained by the available resource levels at that decision point as long as a complete sequence of schedulable activities is found. The procedure is also adapted to various model extensions such as flexible resource requirement levels. The procedure can also be utilized in a dynamic environment where resource absenteeism, activity duration changes and readjustment of the project network configuration are accounted for. Numerical results are obtained for LCBA and three well-reputed dispatching rules to show that considerably better solutions are obtained by the LCBA approach in encouragingly short computation times.

In ıhis note \e propose an iterative scheduling technique which consists of consecutive forward/backward :cheduling pa--..es airne d aı reducing the project duration by smoothing out the project's resource profile. The idea of irer,ııile :-he.lıjlin_e is iniıiated b1 Li and \\rillis in their related paper. The only common point between their ı-hedulin_s tectmique and ıhe one proçrcısed here is the iterative feature. The two techniques differ both İn a}gonithmic a-ipe!- § an,J in ıtıe ua1 actiıiries are selected for scheduling at a decision point. In the technique proposed here actirities are eraluaıe,d t1 uell-repuıed dispatching rules and a conflict based decision-making pro!-ess called Local Consıraint Ba-<ed _\nall-sis ıLCB_\ı. The results on benchmark problems from the literature demonstrate that LCBA specificall1, erploiı-ı the t'leıit,le a!-tili+ ıime ruindou,s provided by the iterative scheduling ıechnique. Keyılords : Project scheduling; Resource al]ocaıion: Heurisıiethree major distinctions of our technique from the procedure by Li and Willis.

In this PaPer, we ProPose a framework for an interactive project scheduling system under limited resources. The fuamework includes a modelling modu]e (ııoopı-) and a scheduling modute (scınouı-gn). The rnodelling module voogı allows üe Decision Maı<er (DM) to develop his/her own model with features such as altemative operating modes for activities; renewable, nonrenewable and/or doubly-constrained resource constraints; general cash flow patterns, related to the rea]ization of activities or events; and progress payments distributed over the project span. The performance criteria include the maximization of Net Present Value (NPV), and either the minimization of maximum tardiness (when a pğect due date exists) or the minimization of the pğect duration (when there is no project due date). The scrnouı-tn is developed on a constraint-based scheduling algoriüım, which is called Local Constraint Based Analysis (ı_cgA.) and which has previously been tested and shown to produce near-optimal results with resPect to the criterion of minimizing project duration, The decisions taken in the sCffiDuLER consist of determining the start times of activities and the specific operating modes in which theY are to be realized. The decisions are taken by activating re]evant essential conditions in ı_csa and in cases where resource conflicts are not resolved, the DM reaches a final decision by testing the altematives proposed by rcsa, through a what-if routine. The scugouısR rePresents a realistic scheduling system which is usefu] not only in the planning Phase of a Pğect but can also be emPloyed during the progress of a project for updating üe project plan, if necessary. An imPortant feature is that the Project plan can be updated by performi.,g İır" l*.t modification of futurc commitments. It is Possible to freeze the activities already scheduled in the near future while admiıting üe changes in üe activity/network information.

Logistics planning in emergency situations involves dispatching commodities (e.g., medical materials and personnel, specialised rescue equipment and rescue teams, food, etc.) to distribution centres in affected areas as soon as possible so that relief operations are accelerated. In this study, a planning model that is to be integrated into a natural disaster logistics Decision Support System is developed. The model addresses the dynamic time-dependent transportation problem that needs to be solved repetitively at given time intervals during ongoing aid delivery. The model regenerates plans incorporating new requests for aid materials, new supplies and transportation means that become available during the current planning time horizon. The plan indicates the optimal mixed pick up and delivery schedules for vehicles within the considered planning time horizon as well as the optimal quantities and types of loads picked up and delivered on these routes.

Decisions on electric power generation and transmission investments may have crucial effects on the development of industrial and residential areas. Decisions made on the infrastructure should have economically beneficial consequences for producers and consumers. The aim of this paper is to propose a model that considers transmission and generation investments simultaneously. The proposed model fills in the gap between models for developing long-term power generation policies and instantaneous power flow models. Unlike other investment models, it explicitly takes the high voltage transmission network into account and the selection of new generation plants located on the interconnected network is made in a more realistic manner considering transmission bottlenecks.

We propose a new metaheuristic, FRACTOP, for global optimization. FRACTOP is based on the geometric partitioning of the feasible region so that search metaheuristics such as Simulated Annealing (SA), or Genetic Algorithms (GA) which are activated in smaller subregions, have increased reliability in locating the global optimum. FRACTOP is able to incorporate any search heuristic devised for global optimization. The main contribution of FRACTOP is that it provides an intelligent guidance (through fuzzy measures) in locating ...