2. You are trying to rob a jewelry store in Salhiya Complex. You go in with an empty 6-ft bag which you wish to fill up with jewels, watches and artifacts from the store. Somehow, you know the following: The estimated resale value of each piece (KD). The ease of packing of each piece (dimensionless). The exact weight of each piece (kg). The estimated time it takes to pack each piece into your bag (s). The approximate volume of each piece (m). Obviously, you wish you maximize the resale value and the ease of packing of each piece, minimize the total weight and packing time (for fast, easy getaway,) all while staying within the maximum volume. Luckily, you know a thing or two about optimization, and realize that this is a multiob- jective optimization problem. Use an EA to solve for the optimum combination of items you will bag using two methods: 1. Use the single-objective GA you've written for your homework. Aggregate all the objectives into a single fitness function that is minimized. Before you do that, normalize every input. This way you avoid the problem of determining appropriate weights for each objective. To enforce the volume constraint, simply penalize solutions (chromosomes) that violate the constraint by "reducing their fitness by double the percent violation. 2. Solve the problem using the Matlab tool gamultiobj, incorporating the actual constraint. Report the optimum solution(s) as well as your codes. Information about the items is given in the attached file. 2. You are trying to rob a jewelry store in Salhiya Complex. You go in with an empty 6-ft bag which you wish to fill up with jewels, watches and artifacts from the store. Somehow, you know the following: The estimated resale value of each piece (KD). The ease of packing of each piece (dimensionless). The exact weight of each piece (kg). The estimated time it takes to pack each piece into your bag (s). The approximate volume of each piece (m). Obviously, you wish you maximize the resale value and the ease of packing of each piece, minimize the total weight and packing time (for fast, easy getaway,) all while staying within the maximum volume. Luckily, you know a thing or two about optimization, and realize that this is a multiob- jective optimization problem. Use an EA to solve for the optimum combination of items you will bag using two methods: 1. Use the single-objective GA you've written for your homework. Aggregate all the objectives into a single fitness function that is minimized. Before you do that, normalize every input. This way you avoid the problem of determining appropriate weights for each objective. To enforce the volume constraint, simply penalize solutions (chromosomes) that violate the constraint by "reducing their fitness by double the percent violation. 2. Solve the problem using the Matlab tool gamultiobj, incorporating the actual constraint. Report the optimum solution(s) as well as your codes. Information about the items is given in the attached file
