ALICE Core is a new application from the construction optioneering company, ALICE Technologies, which I briefly wrote about in my “AI in AEC Updates, 2022” article a couple of years ago. The application I described in that article worked with BIM models for optioneering construction schedules. ALICE Technologies has now introduced a new application that can perform the same functionality using schedules that have been created in Oracle Primavera P6, the leading application used by construction companies for scheduling.
This new application is called ALICE Core, and it joins the earlier flagship application, now called ALICE Pro, in the ALICE Technologies product family. Together, they allow construction companies to fine-tune their construction schedules through analysis and optimization so that they can make the best use of the resources available to them to build the project in the fastest possible time and with the lowest cost (Figure 1). Whereas this capability was earlier limited only to those construction companies using BIM, it is now available to a much wider range of construction firms that use traditional scheduling software for their projects.
Before delving into ALICE Core, let’s look at what the term “construction optioneering” means.
The term “optioneering” refers to an in-depth consideration of various alternatives to find the best or preferred option (see https://en.wiktionary.org/wiki/optioneering). Thus, it is applicable to decision-making in any domain and is not exclusive to the construction industry. However, optioneering seems to be most commonly associated with construction projects, where it refers to a contractor or project team carefully reviewing different construction options to identify the best approach, taking into account not only the cost and the time to build but also factors such as economic, social, and environmental impacts (see https://www.worldconstructiontoday.com/news/what-is-optioneering-in-construction/).
Needless to say, the bigger the project, the larger the number of variables that need to be considered, and the more complex the optioneering process will be (Figure 2). The tools that planners have traditionally relied on to create a construction schedule for the project — such as Microsoft Project, Oracle P6 and even Microsoft Excel — do not allow them to explore a large range of possible options because of the time and the effort that is involved in developing even a single workable plan. To put it simply, the range of possible solutions is simply too large for them to explore without a dedicated tool that does this.
This is precisely the gap that ALICE Technologies is aiming to fill — that of providing a dedicated tool for exploring multiple construction options to develop the optimal one for a project.
The starting point in ALICE Core is to create a new project by importing its P6 schedule in either the XER or XML format. This becomes the baseline schedule in relation to which all other scheduling scenarios can be evaluated. The exploration is visually enabled by showing all the scenarios in the form of colored dots on a scatter plot, with time on the X axis and cost on the Y axis of the graph, as shown in Figure 3. The baseline schedule, which was the original one from the P6 import, is indicated by a green diamond. The plan for the sample project used in this example in the form of its Gantt chart is shown in Figure 4.
In the scatter plot shown in Figure 3, you can see that there are multiple dots corresponding to the scenarios that are listed on the left. This is where the power of ALICE comes in. You can create a new scenario to explore and make any changes to the values of the main scheduling components — Labor, Materials, Equipment, and Milestones — that are different from those of the baseline schedule. ALICE will run through all possible permutations of the schedule with these values and find those that are feasible, indicating them by dots on the scatter plot in the color that is assigned to the scenario. So, for example, I ran a Test scenario by adjusting some values, for which ALICE Core found five possible scheduling solutions, shown in Figure 5 in blue.
To get a better idea of how exactly the multiple solutions found for a single scenario are different from each other, you can select them for comparison. Figure 6 shows three of the five solutions for the Test scenario being compared. The comparison window shows the key metrics of the different solutions and also allows you to delve into the individual parameters. So, for example, you can see that there are only some minor differences in the Labor and Equipment parameters for the three solutions — there are no changes in the other three parameters — which result in them being two distinct solutions, even though they were generated from the same scenario specifications.
A similar comparison can be performed for any of the solutions shown in the scatter plot. So, for example, Figure 7 shows a comparison between solutions belonging to four different scenarios, one of which is the baseline scenario. This allows a greater insight into how different values for the different parameters impact the schedule, enabling extensive “what-if” analysis to be easily performed to fine-tune the schedule.
Additional insights on any solution can be obtained by selecting it to run a detailed analysis. Figure 8 shows the Analyze page for a scenario, showing the specifics of the duration and the cost. These analytics can be further filtered if required to show the details for specific tasks, crews, equipment, materials, and so on.
Additional noteworthy features of ALICE Core include the ability to make a scenario parametric by specifying a range rather than a fixed value for a resource, such as the duration, number of crews, equipment availability, and so on (Figure 9). This is very helpful in exploring parametric activities that can bring down the cost and/or time required to build the project.
Another useful feature is a feasibility check that ALICE Core does when creating a new project from a P6 import. It is able to detect any cyclical logic loops that were made erroneously in P6 as well as any other inconsistencies. These are shown to the user, so they can be corrected in P6 prior to import into ALICE Core.
While ALICE Core has not been developed to duplicate any of the scheduling capabilities in Primavera, it does provide capabilities for tasks such as creating resources, assigning crews to tasks, removing preferential logic, and re-sequencing activities in the project plan (Figure 10), so that users do not have to go back to Primavera to perform these tasks when they are exploring scheduling options in ALICE Core.
And finally, once you have created and fine-tuned a scheduling solution in ALICE Core through the construction optioneering process, you can export it back to Primavera P6. If you now make any changes to the schedule in P6 and bring it back to ALICE Core, it can detect that it is an update, and it only optimizes what has changed. Thus, you can continue the construction optioneering process iteratively, going between P6 and ALICE Core, until the schedule is finalized.
Given the algorithmic nature of scheduling as well as the exponentially large number of ways to build a project — which is true even when there are a limited set of values for key factors such as zoning, equipment, materials, sequencing, and resources, as shown in Figure 2 — the use of automated construction optioneering seems to be a no-brainer. Why would construction companies not want to explore all possible options to build their projects faster and at a lower cost, especially now that there is an application specifically developed for this purpose? And one that also works directly with their P6 schedules?
Amidst all the debate about AI and its questionable impacts on society as a whole as well as in the AEC industry in particular, tools that use cutting edge algorithms and generative design technologies to provide new ways to unequivocally improve design and construction processes in AEC should be welcomed.
Lachmi Khemlani is founder and editor of AECbytes. She has a Ph.D. in Architecture from UC Berkeley, specializing in intelligent building modeling, and consults and writes on AEC technology. She can be reached at lachmi@aecbytes.com.
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